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.gitattributes CHANGED
@@ -57,3 +57,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  # Video files - compressed
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  *.mp4 filter=lfs diff=lfs merge=lfs -text
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  *.webm filter=lfs diff=lfs merge=lfs -text
 
 
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  # Video files - compressed
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  *.mp4 filter=lfs diff=lfs merge=lfs -text
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  *.webm filter=lfs diff=lfs merge=lfs -text
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+ data/ghana_loan.xls filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,46 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ configs:
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+ - config_name: german
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+ data_files:
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+ - split: train
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+ path: train/german_train.csv
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+ - split: test
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+ path: test/german_test.csv
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+ - config_name: ghana
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+ data_files:
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+ - split: train
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+ path: train/modifiedghana_train.csv
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+ - split: test
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+ path: test/modifiedghana_test.csv
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+ - config_name: loan_pred
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+ data_files:
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+ - split: train
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+ path: train/loanpred_train.csv
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+ - split: test
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+ path: test/loanpred_test.csv
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+ - config_name: german_new
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+ data_files:
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+ - split: train
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+ path: new_data/german-train.csv
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+ - split: fewshot
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+ path: new_data/german-fewshot-6.csv
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+ - split: test
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+ path: new_data/german-test.csv
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+ - config_name: ghana_new
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+ data_files:
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+ - split: train
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+ path: new_data/ghana-train.csv
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+ - split: fewshot
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+ path: new_data/ghana-fewshot-6.csv
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+ - split: test
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+ path: new_data/ghana-test.csv
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+ - config_name: loan_pred_new
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+ data_files:
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+ - split: train
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+ path: new_data/loan_pred-train.csv
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+ - split: fewshot
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+ path: new_data/loan_pred-fewshot-6.csv
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+ - split: test
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+ path: new_data/loan_pred-test.csv
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+
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+ ---
Split Notebook.ipynb ADDED
@@ -0,0 +1,462 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "cells": [
3
+ {
4
+ "cell_type": "code",
5
+ "execution_count": 1,
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+ "id": "de47e40f",
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "import pandas as pd\n",
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+ "from sklearn.model_selection import train_test_split\n"
12
+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 37,
17
+ "id": "3a7108a5",
18
+ "metadata": {},
19
+ "outputs": [],
20
+ "source": [
21
+ "def load_data(filepath, data_name = None):\n",
22
+ " if data_name=='german':\n",
23
+ " data = pd.read_csv(filepath)\n",
24
+ " gender_dict = {\n",
25
+ " \"'male single'\": \"male\",\n",
26
+ " \"'female div/dep/mar'\": \"female\",\n",
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+ " \"'male div/sep'\": \"male\",\n",
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+ " \"'male mar/wid'\": \"male\"}\n",
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+ "\n",
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+ " data['gender'] = data['personal_status'].map(gender_dict)\n",
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+ " del data[\"personal_status\"]\n",
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+ " \n",
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+ " S= data['gender']\n",
34
+ " X = data[['checking_status', 'duration', 'credit_history', 'purpose',\n",
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+ " 'credit_amount', 'savings_status', 'employment',\n",
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+ " 'installment_commitment', 'other_parties',\n",
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+ " 'residence_since', 'property_magnitude', 'age', 'other_payment_plans',\n",
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+ " 'housing', 'existing_credits', 'job', 'num_dependents', 'own_telephone',\n",
39
+ " 'foreign_worker']]\n",
40
+ " y = data['class']\n",
41
+ " \n",
42
+ " \n",
43
+ " return S, X, y\n",
44
+ " \n",
45
+ " elif data_name =='loan_predictions':\n",
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+ " data = pd.read_csv(filepath)\n",
47
+ " S= data['Gender']\n",
48
+ " X = data[['Loan_ID', 'Married', 'Dependents', 'Education',\n",
49
+ " 'Self_Employed', 'ApplicantIncome', 'CoapplicantIncome', 'LoanAmount',\n",
50
+ " 'Loan_Amount_Term', 'Credit_History', 'Property_Area']]\n",
51
+ " y = data[ 'Loan_Status']\n",
52
+ " \n",
53
+ " return S, X, y\n",
54
+ " \n",
55
+ " else:\n",
56
+ " data = pd.read_excel(file_path)\n",
57
+ " return data\n",
58
+ "\n",
59
+ " \n",
60
+ "\n",
61
+ " \n",
62
+ " "
63
+ ]
64
+ },
65
+ {
66
+ "cell_type": "code",
67
+ "execution_count": 45,
68
+ "id": "10500e08",
69
+ "metadata": {},
70
+ "outputs": [],
71
+ "source": [
72
+ "# def load_dataset(file_path):\n",
73
+ "# \"\"\"Load the dataset from an Excel file.\"\"\"\n",
74
+ "# return pd.read_excel(file_path)\n",
75
+ "\n",
76
+ "# # Provide the path to your dataset\n",
77
+ "# file_path = 'data/ghana_loan.xls'\n",
78
+ "# df = load_dataset(file_path)\n"
79
+ ]
80
+ },
81
+ {
82
+ "cell_type": "code",
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+ "execution_count": 46,
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+ "id": "14526f43",
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "# df"
89
+ ]
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+ },
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+ {
92
+ "cell_type": "code",
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+ "execution_count": 41,
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+ "id": "68d4a3d6",
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+ "metadata": {},
96
+ "outputs": [
97
+ {
98
+ "ename": "ValueError",
99
+ "evalue": "too many values to unpack (expected 3)",
100
+ "output_type": "error",
101
+ "traceback": [
102
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
103
+ "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
104
+ "Input \u001b[0;32mIn [41]\u001b[0m, in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m filepath \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdata/ghana_loan.xls\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m----> 2\u001b[0m S, X, y \u001b[38;5;241m=\u001b[39m load_data(filepath, data_name \u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m)\n",
105
+ "\u001b[0;31mValueError\u001b[0m: too many values to unpack (expected 3)"
106
+ ]
107
+ }
108
+ ],
109
+ "source": [
110
+ "filepath = 'data/ghana_loan.xls'\n",
111
+ "S, X, y = load_data(filepath, data_name =None)"
112
+ ]
113
+ },
114
+ {
115
+ "cell_type": "code",
116
+ "execution_count": 36,
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+ "id": "97314cec",
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "data": {
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+ "text/html": [
123
+ "<div>\n",
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+ "<style scoped>\n",
125
+ " .dataframe tbody tr th:only-of-type {\n",
126
+ " vertical-align: middle;\n",
127
+ " }\n",
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+ "\n",
129
+ " .dataframe tbody tr th {\n",
130
+ " vertical-align: top;\n",
131
+ " }\n",
132
+ "\n",
133
+ " .dataframe thead th {\n",
134
+ " text-align: right;\n",
135
+ " }\n",
136
+ "</style>\n",
137
+ "<table border=\"1\" class=\"dataframe\">\n",
138
+ " <thead>\n",
139
+ " <tr style=\"text-align: right;\">\n",
140
+ " <th></th>\n",
141
+ " <th>Loan_ID</th>\n",
142
+ " <th>Gender</th>\n",
143
+ " <th>Married</th>\n",
144
+ " <th>Dependents</th>\n",
145
+ " <th>Education</th>\n",
146
+ " <th>Self_Employed</th>\n",
147
+ " <th>ApplicantIncome</th>\n",
148
+ " <th>CoapplicantIncome</th>\n",
149
+ " <th>LoanAmount</th>\n",
150
+ " <th>Loan_Amount_Term</th>\n",
151
+ " <th>Credit_History</th>\n",
152
+ " <th>Property_Area</th>\n",
153
+ " </tr>\n",
154
+ " </thead>\n",
155
+ " <tbody>\n",
156
+ " <tr>\n",
157
+ " <th>0</th>\n",
158
+ " <td>LP001002</td>\n",
159
+ " <td>Male</td>\n",
160
+ " <td>No</td>\n",
161
+ " <td>0</td>\n",
162
+ " <td>Graduate</td>\n",
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+ " <td>No</td>\n",
164
+ " <td>5849</td>\n",
165
+ " <td>0.0</td>\n",
166
+ " <td>NaN</td>\n",
167
+ " <td>360.0</td>\n",
168
+ " <td>1.0</td>\n",
169
+ " <td>Urban</td>\n",
170
+ " </tr>\n",
171
+ " <tr>\n",
172
+ " <th>1</th>\n",
173
+ " <td>LP001003</td>\n",
174
+ " <td>Male</td>\n",
175
+ " <td>Yes</td>\n",
176
+ " <td>1</td>\n",
177
+ " <td>Graduate</td>\n",
178
+ " <td>No</td>\n",
179
+ " <td>4583</td>\n",
180
+ " <td>1508.0</td>\n",
181
+ " <td>128.0</td>\n",
182
+ " <td>360.0</td>\n",
183
+ " <td>1.0</td>\n",
184
+ " <td>Rural</td>\n",
185
+ " </tr>\n",
186
+ " <tr>\n",
187
+ " <th>2</th>\n",
188
+ " <td>LP001005</td>\n",
189
+ " <td>Male</td>\n",
190
+ " <td>Yes</td>\n",
191
+ " <td>0</td>\n",
192
+ " <td>Graduate</td>\n",
193
+ " <td>Yes</td>\n",
194
+ " <td>3000</td>\n",
195
+ " <td>0.0</td>\n",
196
+ " <td>66.0</td>\n",
197
+ " <td>360.0</td>\n",
198
+ " <td>1.0</td>\n",
199
+ " <td>Urban</td>\n",
200
+ " </tr>\n",
201
+ " <tr>\n",
202
+ " <th>3</th>\n",
203
+ " <td>LP001006</td>\n",
204
+ " <td>Male</td>\n",
205
+ " <td>Yes</td>\n",
206
+ " <td>0</td>\n",
207
+ " <td>Not Graduate</td>\n",
208
+ " <td>No</td>\n",
209
+ " <td>2583</td>\n",
210
+ " <td>2358.0</td>\n",
211
+ " <td>120.0</td>\n",
212
+ " <td>360.0</td>\n",
213
+ " <td>1.0</td>\n",
214
+ " <td>Urban</td>\n",
215
+ " </tr>\n",
216
+ " <tr>\n",
217
+ " <th>4</th>\n",
218
+ " <td>LP001008</td>\n",
219
+ " <td>Male</td>\n",
220
+ " <td>No</td>\n",
221
+ " <td>0</td>\n",
222
+ " <td>Graduate</td>\n",
223
+ " <td>No</td>\n",
224
+ " <td>6000</td>\n",
225
+ " <td>0.0</td>\n",
226
+ " <td>141.0</td>\n",
227
+ " <td>360.0</td>\n",
228
+ " <td>1.0</td>\n",
229
+ " <td>Urban</td>\n",
230
+ " </tr>\n",
231
+ " <tr>\n",
232
+ " <th>...</th>\n",
233
+ " <td>...</td>\n",
234
+ " <td>...</td>\n",
235
+ " <td>...</td>\n",
236
+ " <td>...</td>\n",
237
+ " <td>...</td>\n",
238
+ " <td>...</td>\n",
239
+ " <td>...</td>\n",
240
+ " <td>...</td>\n",
241
+ " <td>...</td>\n",
242
+ " <td>...</td>\n",
243
+ " <td>...</td>\n",
244
+ " <td>...</td>\n",
245
+ " </tr>\n",
246
+ " <tr>\n",
247
+ " <th>609</th>\n",
248
+ " <td>LP002978</td>\n",
249
+ " <td>Female</td>\n",
250
+ " <td>No</td>\n",
251
+ " <td>0</td>\n",
252
+ " <td>Graduate</td>\n",
253
+ " <td>No</td>\n",
254
+ " <td>2900</td>\n",
255
+ " <td>0.0</td>\n",
256
+ " <td>71.0</td>\n",
257
+ " <td>360.0</td>\n",
258
+ " <td>1.0</td>\n",
259
+ " <td>Rural</td>\n",
260
+ " </tr>\n",
261
+ " <tr>\n",
262
+ " <th>610</th>\n",
263
+ " <td>LP002979</td>\n",
264
+ " <td>Male</td>\n",
265
+ " <td>Yes</td>\n",
266
+ " <td>3+</td>\n",
267
+ " <td>Graduate</td>\n",
268
+ " <td>No</td>\n",
269
+ " <td>4106</td>\n",
270
+ " <td>0.0</td>\n",
271
+ " <td>40.0</td>\n",
272
+ " <td>180.0</td>\n",
273
+ " <td>1.0</td>\n",
274
+ " <td>Rural</td>\n",
275
+ " </tr>\n",
276
+ " <tr>\n",
277
+ " <th>611</th>\n",
278
+ " <td>LP002983</td>\n",
279
+ " <td>Male</td>\n",
280
+ " <td>Yes</td>\n",
281
+ " <td>1</td>\n",
282
+ " <td>Graduate</td>\n",
283
+ " <td>No</td>\n",
284
+ " <td>8072</td>\n",
285
+ " <td>240.0</td>\n",
286
+ " <td>253.0</td>\n",
287
+ " <td>360.0</td>\n",
288
+ " <td>1.0</td>\n",
289
+ " <td>Urban</td>\n",
290
+ " </tr>\n",
291
+ " <tr>\n",
292
+ " <th>612</th>\n",
293
+ " <td>LP002984</td>\n",
294
+ " <td>Male</td>\n",
295
+ " <td>Yes</td>\n",
296
+ " <td>2</td>\n",
297
+ " <td>Graduate</td>\n",
298
+ " <td>No</td>\n",
299
+ " <td>7583</td>\n",
300
+ " <td>0.0</td>\n",
301
+ " <td>187.0</td>\n",
302
+ " <td>360.0</td>\n",
303
+ " <td>1.0</td>\n",
304
+ " <td>Urban</td>\n",
305
+ " </tr>\n",
306
+ " <tr>\n",
307
+ " <th>613</th>\n",
308
+ " <td>LP002990</td>\n",
309
+ " <td>Female</td>\n",
310
+ " <td>No</td>\n",
311
+ " <td>0</td>\n",
312
+ " <td>Graduate</td>\n",
313
+ " <td>Yes</td>\n",
314
+ " <td>4583</td>\n",
315
+ " <td>0.0</td>\n",
316
+ " <td>133.0</td>\n",
317
+ " <td>360.0</td>\n",
318
+ " <td>0.0</td>\n",
319
+ " <td>Semiurban</td>\n",
320
+ " </tr>\n",
321
+ " </tbody>\n",
322
+ "</table>\n",
323
+ "<p>614 rows × 12 columns</p>\n",
324
+ "</div>"
325
+ ],
326
+ "text/plain": [
327
+ " Loan_ID Gender Married Dependents Education Self_Employed \\\n",
328
+ "0 LP001002 Male No 0 Graduate No \n",
329
+ "1 LP001003 Male Yes 1 Graduate No \n",
330
+ "2 LP001005 Male Yes 0 Graduate Yes \n",
331
+ "3 LP001006 Male Yes 0 Not Graduate No \n",
332
+ "4 LP001008 Male No 0 Graduate No \n",
333
+ ".. ... ... ... ... ... ... \n",
334
+ "609 LP002978 Female No 0 Graduate No \n",
335
+ "610 LP002979 Male Yes 3+ Graduate No \n",
336
+ "611 LP002983 Male Yes 1 Graduate No \n",
337
+ "612 LP002984 Male Yes 2 Graduate No \n",
338
+ "613 LP002990 Female No 0 Graduate Yes \n",
339
+ "\n",
340
+ " ApplicantIncome CoapplicantIncome LoanAmount Loan_Amount_Term \\\n",
341
+ "0 5849 0.0 NaN 360.0 \n",
342
+ "1 4583 1508.0 128.0 360.0 \n",
343
+ "2 3000 0.0 66.0 360.0 \n",
344
+ "3 2583 2358.0 120.0 360.0 \n",
345
+ "4 6000 0.0 141.0 360.0 \n",
346
+ ".. ... ... ... ... \n",
347
+ "609 2900 0.0 71.0 360.0 \n",
348
+ "610 4106 0.0 40.0 180.0 \n",
349
+ "611 8072 240.0 253.0 360.0 \n",
350
+ "612 7583 0.0 187.0 360.0 \n",
351
+ "613 4583 0.0 133.0 360.0 \n",
352
+ "\n",
353
+ " Credit_History Property_Area \n",
354
+ "0 1.0 Urban \n",
355
+ "1 1.0 Rural \n",
356
+ "2 1.0 Urban \n",
357
+ "3 1.0 Urban \n",
358
+ "4 1.0 Urban \n",
359
+ ".. ... ... \n",
360
+ "609 1.0 Rural \n",
361
+ "610 1.0 Rural \n",
362
+ "611 1.0 Urban \n",
363
+ "612 1.0 Urban \n",
364
+ "613 0.0 Semiurban \n",
365
+ "\n",
366
+ "[614 rows x 12 columns]"
367
+ ]
368
+ },
369
+ "execution_count": 36,
370
+ "metadata": {},
371
+ "output_type": "execute_result"
372
+ }
373
+ ],
374
+ "source": []
375
+ },
376
+ {
377
+ "cell_type": "code",
378
+ "execution_count": 21,
379
+ "id": "422d9c7c",
380
+ "metadata": {},
381
+ "outputs": [],
382
+ "source": [
383
+ "# S = df['Gender']\n",
384
+ "# X = df[['Loan_ID', 'Gender', 'Married', 'Dependents', 'Education',\n",
385
+ "# 'Self_Employed', 'ApplicantIncome', 'CoapplicantIncome', 'LoanAmount',\n",
386
+ "# 'Loan_Amount_Term', 'Credit_History', 'Property_Area']]\n",
387
+ "# y = df[ 'Loan_Status']"
388
+ ]
389
+ },
390
+ {
391
+ "cell_type": "code",
392
+ "execution_count": 22,
393
+ "id": "4bb62629",
394
+ "metadata": {},
395
+ "outputs": [],
396
+ "source": [
397
+ "S_train, S_test, X_train, X_test, y_train, y_test = train_test_split(S, X, y, test_size=0.2, random_state=42)"
398
+ ]
399
+ },
400
+ {
401
+ "cell_type": "code",
402
+ "execution_count": 23,
403
+ "id": "0fab58f1",
404
+ "metadata": {},
405
+ "outputs": [
406
+ {
407
+ "name": "stdout",
408
+ "output_type": "stream",
409
+ "text": [
410
+ "Datasets saved to train.csv and test.csv\n"
411
+ ]
412
+ }
413
+ ],
414
+ "source": [
415
+ "def save_to_csv(S_train, S_test, X_train, X_test, y_train, y_test, train_file_name, test_file_name):\n",
416
+ " \"\"\"Save the train and test sets to CSV files.\"\"\"\n",
417
+ " train = pd.concat([S_train, X_train, y_train], axis=1)\n",
418
+ " test = pd.concat([S_test, X_test, y_test], axis=1)\n",
419
+ " \n",
420
+ " train.to_csv(f'train/{train_file_name}', index=False)\n",
421
+ " test.to_csv(f'test/{test_file_name}', index=False)\n",
422
+ "\n",
423
+ "# Specify the file names\n",
424
+ "train_file_name = 'loanpred_train.csv'\n",
425
+ "test_file_name = 'loanpred_test.csv'\n",
426
+ "# Save the datasets to CSV files\n",
427
+ "save_to_csv(S_train, S_test, X_train, X_test, y_train, y_test, train_file_name, test_file_name)\n",
428
+ "\n",
429
+ "print(\"Datasets saved to train.csv and test.csv\")\n"
430
+ ]
431
+ },
432
+ {
433
+ "cell_type": "code",
434
+ "execution_count": null,
435
+ "id": "adccf7b2",
436
+ "metadata": {},
437
+ "outputs": [],
438
+ "source": []
439
+ }
440
+ ],
441
+ "metadata": {
442
+ "kernelspec": {
443
+ "display_name": "Python 3 (ipykernel)",
444
+ "language": "python",
445
+ "name": "python3"
446
+ },
447
+ "language_info": {
448
+ "codemirror_mode": {
449
+ "name": "ipython",
450
+ "version": 3
451
+ },
452
+ "file_extension": ".py",
453
+ "mimetype": "text/x-python",
454
+ "name": "python",
455
+ "nbconvert_exporter": "python",
456
+ "pygments_lexer": "ipython3",
457
+ "version": "3.9.12"
458
+ }
459
+ },
460
+ "nbformat": 4,
461
+ "nbformat_minor": 5
462
+ }
data/german_credit.csv ADDED
The diff for this file is too large to render. See raw diff
 
data/ghana_loan.xls ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:461fd7900e6b160a6cf2c64e42299f6c5de2d36f78c2be7738eeaf91c7e0a0fc
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+ size 224256
data/loan_predictions.csv ADDED
@@ -0,0 +1,615 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Loan_ID,Gender,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_Status
2
+ LP001002,Male,No,0,Graduate,No,5849,0,,360,1,Urban,Y
3
+ LP001003,Male,Yes,1,Graduate,No,4583,1508,128,360,1,Rural,N
4
+ LP001005,Male,Yes,0,Graduate,Yes,3000,0,66,360,1,Urban,Y
5
+ LP001006,Male,Yes,0,Not Graduate,No,2583,2358,120,360,1,Urban,Y
6
+ LP001008,Male,No,0,Graduate,No,6000,0,141,360,1,Urban,Y
7
+ LP001011,Male,Yes,2,Graduate,Yes,5417,4196,267,360,1,Urban,Y
8
+ LP001013,Male,Yes,0,Not Graduate,No,2333,1516,95,360,1,Urban,Y
9
+ LP001014,Male,Yes,3+,Graduate,No,3036,2504,158,360,0,Semiurban,N
10
+ LP001018,Male,Yes,2,Graduate,No,4006,1526,168,360,1,Urban,Y
11
+ LP001020,Male,Yes,1,Graduate,No,12841,10968,349,360,1,Semiurban,N
12
+ LP001024,Male,Yes,2,Graduate,No,3200,700,70,360,1,Urban,Y
13
+ LP001027,Male,Yes,2,Graduate,,2500,1840,109,360,1,Urban,Y
14
+ LP001028,Male,Yes,2,Graduate,No,3073,8106,200,360,1,Urban,Y
15
+ LP001029,Male,No,0,Graduate,No,1853,2840,114,360,1,Rural,N
16
+ LP001030,Male,Yes,2,Graduate,No,1299,1086,17,120,1,Urban,Y
17
+ LP001032,Male,No,0,Graduate,No,4950,0,125,360,1,Urban,Y
18
+ LP001034,Male,No,1,Not Graduate,No,3596,0,100,240,,Urban,Y
19
+ LP001036,Female,No,0,Graduate,No,3510,0,76,360,0,Urban,N
20
+ LP001038,Male,Yes,0,Not Graduate,No,4887,0,133,360,1,Rural,N
21
+ LP001041,Male,Yes,0,Graduate,,2600,3500,115,,1,Urban,Y
22
+ LP001043,Male,Yes,0,Not Graduate,No,7660,0,104,360,0,Urban,N
23
+ LP001046,Male,Yes,1,Graduate,No,5955,5625,315,360,1,Urban,Y
24
+ LP001047,Male,Yes,0,Not Graduate,No,2600,1911,116,360,0,Semiurban,N
25
+ LP001050,,Yes,2,Not Graduate,No,3365,1917,112,360,0,Rural,N
26
+ LP001052,Male,Yes,1,Graduate,,3717,2925,151,360,,Semiurban,N
27
+ LP001066,Male,Yes,0,Graduate,Yes,9560,0,191,360,1,Semiurban,Y
28
+ LP001068,Male,Yes,0,Graduate,No,2799,2253,122,360,1,Semiurban,Y
29
+ LP001073,Male,Yes,2,Not Graduate,No,4226,1040,110,360,1,Urban,Y
30
+ LP001086,Male,No,0,Not Graduate,No,1442,0,35,360,1,Urban,N
31
+ LP001087,Female,No,2,Graduate,,3750,2083,120,360,1,Semiurban,Y
32
+ LP001091,Male,Yes,1,Graduate,,4166,3369,201,360,,Urban,N
33
+ LP001095,Male,No,0,Graduate,No,3167,0,74,360,1,Urban,N
34
+ LP001097,Male,No,1,Graduate,Yes,4692,0,106,360,1,Rural,N
35
+ LP001098,Male,Yes,0,Graduate,No,3500,1667,114,360,1,Semiurban,Y
36
+ LP001100,Male,No,3+,Graduate,No,12500,3000,320,360,1,Rural,N
37
+ LP001106,Male,Yes,0,Graduate,No,2275,2067,,360,1,Urban,Y
38
+ LP001109,Male,Yes,0,Graduate,No,1828,1330,100,,0,Urban,N
39
+ LP001112,Female,Yes,0,Graduate,No,3667,1459,144,360,1,Semiurban,Y
40
+ LP001114,Male,No,0,Graduate,No,4166,7210,184,360,1,Urban,Y
41
+ LP001116,Male,No,0,Not Graduate,No,3748,1668,110,360,1,Semiurban,Y
42
+ LP001119,Male,No,0,Graduate,No,3600,0,80,360,1,Urban,N
43
+ LP001120,Male,No,0,Graduate,No,1800,1213,47,360,1,Urban,Y
44
+ LP001123,Male,Yes,0,Graduate,No,2400,0,75,360,,Urban,Y
45
+ LP001131,Male,Yes,0,Graduate,No,3941,2336,134,360,1,Semiurban,Y
46
+ LP001136,Male,Yes,0,Not Graduate,Yes,4695,0,96,,1,Urban,Y
47
+ LP001137,Female,No,0,Graduate,No,3410,0,88,,1,Urban,Y
48
+ LP001138,Male,Yes,1,Graduate,No,5649,0,44,360,1,Urban,Y
49
+ LP001144,Male,Yes,0,Graduate,No,5821,0,144,360,1,Urban,Y
50
+ LP001146,Female,Yes,0,Graduate,No,2645,3440,120,360,0,Urban,N
51
+ LP001151,Female,No,0,Graduate,No,4000,2275,144,360,1,Semiurban,Y
52
+ LP001155,Female,Yes,0,Not Graduate,No,1928,1644,100,360,1,Semiurban,Y
53
+ LP001157,Female,No,0,Graduate,No,3086,0,120,360,1,Semiurban,Y
54
+ LP001164,Female,No,0,Graduate,No,4230,0,112,360,1,Semiurban,N
55
+ LP001179,Male,Yes,2,Graduate,No,4616,0,134,360,1,Urban,N
56
+ LP001186,Female,Yes,1,Graduate,Yes,11500,0,286,360,0,Urban,N
57
+ LP001194,Male,Yes,2,Graduate,No,2708,1167,97,360,1,Semiurban,Y
58
+ LP001195,Male,Yes,0,Graduate,No,2132,1591,96,360,1,Semiurban,Y
59
+ LP001197,Male,Yes,0,Graduate,No,3366,2200,135,360,1,Rural,N
60
+ LP001198,Male,Yes,1,Graduate,No,8080,2250,180,360,1,Urban,Y
61
+ LP001199,Male,Yes,2,Not Graduate,No,3357,2859,144,360,1,Urban,Y
62
+ LP001205,Male,Yes,0,Graduate,No,2500,3796,120,360,1,Urban,Y
63
+ LP001206,Male,Yes,3+,Graduate,No,3029,0,99,360,1,Urban,Y
64
+ LP001207,Male,Yes,0,Not Graduate,Yes,2609,3449,165,180,0,Rural,N
65
+ LP001213,Male,Yes,1,Graduate,No,4945,0,,360,0,Rural,N
66
+ LP001222,Female,No,0,Graduate,No,4166,0,116,360,0,Semiurban,N
67
+ LP001225,Male,Yes,0,Graduate,No,5726,4595,258,360,1,Semiurban,N
68
+ LP001228,Male,No,0,Not Graduate,No,3200,2254,126,180,0,Urban,N
69
+ LP001233,Male,Yes,1,Graduate,No,10750,0,312,360,1,Urban,Y
70
+ LP001238,Male,Yes,3+,Not Graduate,Yes,7100,0,125,60,1,Urban,Y
71
+ LP001241,Female,No,0,Graduate,No,4300,0,136,360,0,Semiurban,N
72
+ LP001243,Male,Yes,0,Graduate,No,3208,3066,172,360,1,Urban,Y
73
+ LP001245,Male,Yes,2,Not Graduate,Yes,1875,1875,97,360,1,Semiurban,Y
74
+ LP001248,Male,No,0,Graduate,No,3500,0,81,300,1,Semiurban,Y
75
+ LP001250,Male,Yes,3+,Not Graduate,No,4755,0,95,,0,Semiurban,N
76
+ LP001253,Male,Yes,3+,Graduate,Yes,5266,1774,187,360,1,Semiurban,Y
77
+ LP001255,Male,No,0,Graduate,No,3750,0,113,480,1,Urban,N
78
+ LP001256,Male,No,0,Graduate,No,3750,4750,176,360,1,Urban,N
79
+ LP001259,Male,Yes,1,Graduate,Yes,1000,3022,110,360,1,Urban,N
80
+ LP001263,Male,Yes,3+,Graduate,No,3167,4000,180,300,0,Semiurban,N
81
+ LP001264,Male,Yes,3+,Not Graduate,Yes,3333,2166,130,360,,Semiurban,Y
82
+ LP001265,Female,No,0,Graduate,No,3846,0,111,360,1,Semiurban,Y
83
+ LP001266,Male,Yes,1,Graduate,Yes,2395,0,,360,1,Semiurban,Y
84
+ LP001267,Female,Yes,2,Graduate,No,1378,1881,167,360,1,Urban,N
85
+ LP001273,Male,Yes,0,Graduate,No,6000,2250,265,360,,Semiurban,N
86
+ LP001275,Male,Yes,1,Graduate,No,3988,0,50,240,1,Urban,Y
87
+ LP001279,Male,No,0,Graduate,No,2366,2531,136,360,1,Semiurban,Y
88
+ LP001280,Male,Yes,2,Not Graduate,No,3333,2000,99,360,,Semiurban,Y
89
+ LP001282,Male,Yes,0,Graduate,No,2500,2118,104,360,1,Semiurban,Y
90
+ LP001289,Male,No,0,Graduate,No,8566,0,210,360,1,Urban,Y
91
+ LP001310,Male,Yes,0,Graduate,No,5695,4167,175,360,1,Semiurban,Y
92
+ LP001316,Male,Yes,0,Graduate,No,2958,2900,131,360,1,Semiurban,Y
93
+ LP001318,Male,Yes,2,Graduate,No,6250,5654,188,180,1,Semiurban,Y
94
+ LP001319,Male,Yes,2,Not Graduate,No,3273,1820,81,360,1,Urban,Y
95
+ LP001322,Male,No,0,Graduate,No,4133,0,122,360,1,Semiurban,Y
96
+ LP001325,Male,No,0,Not Graduate,No,3620,0,25,120,1,Semiurban,Y
97
+ LP001326,Male,No,0,Graduate,,6782,0,,360,,Urban,N
98
+ LP001327,Female,Yes,0,Graduate,No,2484,2302,137,360,1,Semiurban,Y
99
+ LP001333,Male,Yes,0,Graduate,No,1977,997,50,360,1,Semiurban,Y
100
+ LP001334,Male,Yes,0,Not Graduate,No,4188,0,115,180,1,Semiurban,Y
101
+ LP001343,Male,Yes,0,Graduate,No,1759,3541,131,360,1,Semiurban,Y
102
+ LP001345,Male,Yes,2,Not Graduate,No,4288,3263,133,180,1,Urban,Y
103
+ LP001349,Male,No,0,Graduate,No,4843,3806,151,360,1,Semiurban,Y
104
+ LP001350,Male,Yes,,Graduate,No,13650,0,,360,1,Urban,Y
105
+ LP001356,Male,Yes,0,Graduate,No,4652,3583,,360,1,Semiurban,Y
106
+ LP001357,Male,,,Graduate,No,3816,754,160,360,1,Urban,Y
107
+ LP001367,Male,Yes,1,Graduate,No,3052,1030,100,360,1,Urban,Y
108
+ LP001369,Male,Yes,2,Graduate,No,11417,1126,225,360,1,Urban,Y
109
+ LP001370,Male,No,0,Not Graduate,,7333,0,120,360,1,Rural,N
110
+ LP001379,Male,Yes,2,Graduate,No,3800,3600,216,360,0,Urban,N
111
+ LP001384,Male,Yes,3+,Not Graduate,No,2071,754,94,480,1,Semiurban,Y
112
+ LP001385,Male,No,0,Graduate,No,5316,0,136,360,1,Urban,Y
113
+ LP001387,Female,Yes,0,Graduate,,2929,2333,139,360,1,Semiurban,Y
114
+ LP001391,Male,Yes,0,Not Graduate,No,3572,4114,152,,0,Rural,N
115
+ LP001392,Female,No,1,Graduate,Yes,7451,0,,360,1,Semiurban,Y
116
+ LP001398,Male,No,0,Graduate,,5050,0,118,360,1,Semiurban,Y
117
+ LP001401,Male,Yes,1,Graduate,No,14583,0,185,180,1,Rural,Y
118
+ LP001404,Female,Yes,0,Graduate,No,3167,2283,154,360,1,Semiurban,Y
119
+ LP001405,Male,Yes,1,Graduate,No,2214,1398,85,360,,Urban,Y
120
+ LP001421,Male,Yes,0,Graduate,No,5568,2142,175,360,1,Rural,N
121
+ LP001422,Female,No,0,Graduate,No,10408,0,259,360,1,Urban,Y
122
+ LP001426,Male,Yes,,Graduate,No,5667,2667,180,360,1,Rural,Y
123
+ LP001430,Female,No,0,Graduate,No,4166,0,44,360,1,Semiurban,Y
124
+ LP001431,Female,No,0,Graduate,No,2137,8980,137,360,0,Semiurban,Y
125
+ LP001432,Male,Yes,2,Graduate,No,2957,0,81,360,1,Semiurban,Y
126
+ LP001439,Male,Yes,0,Not Graduate,No,4300,2014,194,360,1,Rural,Y
127
+ LP001443,Female,No,0,Graduate,No,3692,0,93,360,,Rural,Y
128
+ LP001448,,Yes,3+,Graduate,No,23803,0,370,360,1,Rural,Y
129
+ LP001449,Male,No,0,Graduate,No,3865,1640,,360,1,Rural,Y
130
+ LP001451,Male,Yes,1,Graduate,Yes,10513,3850,160,180,0,Urban,N
131
+ LP001465,Male,Yes,0,Graduate,No,6080,2569,182,360,,Rural,N
132
+ LP001469,Male,No,0,Graduate,Yes,20166,0,650,480,,Urban,Y
133
+ LP001473,Male,No,0,Graduate,No,2014,1929,74,360,1,Urban,Y
134
+ LP001478,Male,No,0,Graduate,No,2718,0,70,360,1,Semiurban,Y
135
+ LP001482,Male,Yes,0,Graduate,Yes,3459,0,25,120,1,Semiurban,Y
136
+ LP001487,Male,No,0,Graduate,No,4895,0,102,360,1,Semiurban,Y
137
+ LP001488,Male,Yes,3+,Graduate,No,4000,7750,290,360,1,Semiurban,N
138
+ LP001489,Female,Yes,0,Graduate,No,4583,0,84,360,1,Rural,N
139
+ LP001491,Male,Yes,2,Graduate,Yes,3316,3500,88,360,1,Urban,Y
140
+ LP001492,Male,No,0,Graduate,No,14999,0,242,360,0,Semiurban,N
141
+ LP001493,Male,Yes,2,Not Graduate,No,4200,1430,129,360,1,Rural,N
142
+ LP001497,Male,Yes,2,Graduate,No,5042,2083,185,360,1,Rural,N
143
+ LP001498,Male,No,0,Graduate,No,5417,0,168,360,1,Urban,Y
144
+ LP001504,Male,No,0,Graduate,Yes,6950,0,175,180,1,Semiurban,Y
145
+ LP001507,Male,Yes,0,Graduate,No,2698,2034,122,360,1,Semiurban,Y
146
+ LP001508,Male,Yes,2,Graduate,No,11757,0,187,180,1,Urban,Y
147
+ LP001514,Female,Yes,0,Graduate,No,2330,4486,100,360,1,Semiurban,Y
148
+ LP001516,Female,Yes,2,Graduate,No,14866,0,70,360,1,Urban,Y
149
+ LP001518,Male,Yes,1,Graduate,No,1538,1425,30,360,1,Urban,Y
150
+ LP001519,Female,No,0,Graduate,No,10000,1666,225,360,1,Rural,N
151
+ LP001520,Male,Yes,0,Graduate,No,4860,830,125,360,1,Semiurban,Y
152
+ LP001528,Male,No,0,Graduate,No,6277,0,118,360,0,Rural,N
153
+ LP001529,Male,Yes,0,Graduate,Yes,2577,3750,152,360,1,Rural,Y
154
+ LP001531,Male,No,0,Graduate,No,9166,0,244,360,1,Urban,N
155
+ LP001532,Male,Yes,2,Not Graduate,No,2281,0,113,360,1,Rural,N
156
+ LP001535,Male,No,0,Graduate,No,3254,0,50,360,1,Urban,Y
157
+ LP001536,Male,Yes,3+,Graduate,No,39999,0,600,180,0,Semiurban,Y
158
+ LP001541,Male,Yes,1,Graduate,No,6000,0,160,360,,Rural,Y
159
+ LP001543,Male,Yes,1,Graduate,No,9538,0,187,360,1,Urban,Y
160
+ LP001546,Male,No,0,Graduate,,2980,2083,120,360,1,Rural,Y
161
+ LP001552,Male,Yes,0,Graduate,No,4583,5625,255,360,1,Semiurban,Y
162
+ LP001560,Male,Yes,0,Not Graduate,No,1863,1041,98,360,1,Semiurban,Y
163
+ LP001562,Male,Yes,0,Graduate,No,7933,0,275,360,1,Urban,N
164
+ LP001565,Male,Yes,1,Graduate,No,3089,1280,121,360,0,Semiurban,N
165
+ LP001570,Male,Yes,2,Graduate,No,4167,1447,158,360,1,Rural,Y
166
+ LP001572,Male,Yes,0,Graduate,No,9323,0,75,180,1,Urban,Y
167
+ LP001574,Male,Yes,0,Graduate,No,3707,3166,182,,1,Rural,Y
168
+ LP001577,Female,Yes,0,Graduate,No,4583,0,112,360,1,Rural,N
169
+ LP001578,Male,Yes,0,Graduate,No,2439,3333,129,360,1,Rural,Y
170
+ LP001579,Male,No,0,Graduate,No,2237,0,63,480,0,Semiurban,N
171
+ LP001580,Male,Yes,2,Graduate,No,8000,0,200,360,1,Semiurban,Y
172
+ LP001581,Male,Yes,0,Not Graduate,,1820,1769,95,360,1,Rural,Y
173
+ LP001585,,Yes,3+,Graduate,No,51763,0,700,300,1,Urban,Y
174
+ LP001586,Male,Yes,3+,Not Graduate,No,3522,0,81,180,1,Rural,N
175
+ LP001594,Male,Yes,0,Graduate,No,5708,5625,187,360,1,Semiurban,Y
176
+ LP001603,Male,Yes,0,Not Graduate,Yes,4344,736,87,360,1,Semiurban,N
177
+ LP001606,Male,Yes,0,Graduate,No,3497,1964,116,360,1,Rural,Y
178
+ LP001608,Male,Yes,2,Graduate,No,2045,1619,101,360,1,Rural,Y
179
+ LP001610,Male,Yes,3+,Graduate,No,5516,11300,495,360,0,Semiurban,N
180
+ LP001616,Male,Yes,1,Graduate,No,3750,0,116,360,1,Semiurban,Y
181
+ LP001630,Male,No,0,Not Graduate,No,2333,1451,102,480,0,Urban,N
182
+ LP001633,Male,Yes,1,Graduate,No,6400,7250,180,360,0,Urban,N
183
+ LP001634,Male,No,0,Graduate,No,1916,5063,67,360,,Rural,N
184
+ LP001636,Male,Yes,0,Graduate,No,4600,0,73,180,1,Semiurban,Y
185
+ LP001637,Male,Yes,1,Graduate,No,33846,0,260,360,1,Semiurban,N
186
+ LP001639,Female,Yes,0,Graduate,No,3625,0,108,360,1,Semiurban,Y
187
+ LP001640,Male,Yes,0,Graduate,Yes,39147,4750,120,360,1,Semiurban,Y
188
+ LP001641,Male,Yes,1,Graduate,Yes,2178,0,66,300,0,Rural,N
189
+ LP001643,Male,Yes,0,Graduate,No,2383,2138,58,360,,Rural,Y
190
+ LP001644,,Yes,0,Graduate,Yes,674,5296,168,360,1,Rural,Y
191
+ LP001647,Male,Yes,0,Graduate,No,9328,0,188,180,1,Rural,Y
192
+ LP001653,Male,No,0,Not Graduate,No,4885,0,48,360,1,Rural,Y
193
+ LP001656,Male,No,0,Graduate,No,12000,0,164,360,1,Semiurban,N
194
+ LP001657,Male,Yes,0,Not Graduate,No,6033,0,160,360,1,Urban,N
195
+ LP001658,Male,No,0,Graduate,No,3858,0,76,360,1,Semiurban,Y
196
+ LP001664,Male,No,0,Graduate,No,4191,0,120,360,1,Rural,Y
197
+ LP001665,Male,Yes,1,Graduate,No,3125,2583,170,360,1,Semiurban,N
198
+ LP001666,Male,No,0,Graduate,No,8333,3750,187,360,1,Rural,Y
199
+ LP001669,Female,No,0,Not Graduate,No,1907,2365,120,,1,Urban,Y
200
+ LP001671,Female,Yes,0,Graduate,No,3416,2816,113,360,,Semiurban,Y
201
+ LP001673,Male,No,0,Graduate,Yes,11000,0,83,360,1,Urban,N
202
+ LP001674,Male,Yes,1,Not Graduate,No,2600,2500,90,360,1,Semiurban,Y
203
+ LP001677,Male,No,2,Graduate,No,4923,0,166,360,0,Semiurban,Y
204
+ LP001682,Male,Yes,3+,Not Graduate,No,3992,0,,180,1,Urban,N
205
+ LP001688,Male,Yes,1,Not Graduate,No,3500,1083,135,360,1,Urban,Y
206
+ LP001691,Male,Yes,2,Not Graduate,No,3917,0,124,360,1,Semiurban,Y
207
+ LP001692,Female,No,0,Not Graduate,No,4408,0,120,360,1,Semiurban,Y
208
+ LP001693,Female,No,0,Graduate,No,3244,0,80,360,1,Urban,Y
209
+ LP001698,Male,No,0,Not Graduate,No,3975,2531,55,360,1,Rural,Y
210
+ LP001699,Male,No,0,Graduate,No,2479,0,59,360,1,Urban,Y
211
+ LP001702,Male,No,0,Graduate,No,3418,0,127,360,1,Semiurban,N
212
+ LP001708,Female,No,0,Graduate,No,10000,0,214,360,1,Semiurban,N
213
+ LP001711,Male,Yes,3+,Graduate,No,3430,1250,128,360,0,Semiurban,N
214
+ LP001713,Male,Yes,1,Graduate,Yes,7787,0,240,360,1,Urban,Y
215
+ LP001715,Male,Yes,3+,Not Graduate,Yes,5703,0,130,360,1,Rural,Y
216
+ LP001716,Male,Yes,0,Graduate,No,3173,3021,137,360,1,Urban,Y
217
+ LP001720,Male,Yes,3+,Not Graduate,No,3850,983,100,360,1,Semiurban,Y
218
+ LP001722,Male,Yes,0,Graduate,No,150,1800,135,360,1,Rural,N
219
+ LP001726,Male,Yes,0,Graduate,No,3727,1775,131,360,1,Semiurban,Y
220
+ LP001732,Male,Yes,2,Graduate,,5000,0,72,360,0,Semiurban,N
221
+ LP001734,Female,Yes,2,Graduate,No,4283,2383,127,360,,Semiurban,Y
222
+ LP001736,Male,Yes,0,Graduate,No,2221,0,60,360,0,Urban,N
223
+ LP001743,Male,Yes,2,Graduate,No,4009,1717,116,360,1,Semiurban,Y
224
+ LP001744,Male,No,0,Graduate,No,2971,2791,144,360,1,Semiurban,Y
225
+ LP001749,Male,Yes,0,Graduate,No,7578,1010,175,,1,Semiurban,Y
226
+ LP001750,Male,Yes,0,Graduate,No,6250,0,128,360,1,Semiurban,Y
227
+ LP001751,Male,Yes,0,Graduate,No,3250,0,170,360,1,Rural,N
228
+ LP001754,Male,Yes,,Not Graduate,Yes,4735,0,138,360,1,Urban,N
229
+ LP001758,Male,Yes,2,Graduate,No,6250,1695,210,360,1,Semiurban,Y
230
+ LP001760,Male,,,Graduate,No,4758,0,158,480,1,Semiurban,Y
231
+ LP001761,Male,No,0,Graduate,Yes,6400,0,200,360,1,Rural,Y
232
+ LP001765,Male,Yes,1,Graduate,No,2491,2054,104,360,1,Semiurban,Y
233
+ LP001768,Male,Yes,0,Graduate,,3716,0,42,180,1,Rural,Y
234
+ LP001770,Male,No,0,Not Graduate,No,3189,2598,120,,1,Rural,Y
235
+ LP001776,Female,No,0,Graduate,No,8333,0,280,360,1,Semiurban,Y
236
+ LP001778,Male,Yes,1,Graduate,No,3155,1779,140,360,1,Semiurban,Y
237
+ LP001784,Male,Yes,1,Graduate,No,5500,1260,170,360,1,Rural,Y
238
+ LP001786,Male,Yes,0,Graduate,,5746,0,255,360,,Urban,N
239
+ LP001788,Female,No,0,Graduate,Yes,3463,0,122,360,,Urban,Y
240
+ LP001790,Female,No,1,Graduate,No,3812,0,112,360,1,Rural,Y
241
+ LP001792,Male,Yes,1,Graduate,No,3315,0,96,360,1,Semiurban,Y
242
+ LP001798,Male,Yes,2,Graduate,No,5819,5000,120,360,1,Rural,Y
243
+ LP001800,Male,Yes,1,Not Graduate,No,2510,1983,140,180,1,Urban,N
244
+ LP001806,Male,No,0,Graduate,No,2965,5701,155,60,1,Urban,Y
245
+ LP001807,Male,Yes,2,Graduate,Yes,6250,1300,108,360,1,Rural,Y
246
+ LP001811,Male,Yes,0,Not Graduate,No,3406,4417,123,360,1,Semiurban,Y
247
+ LP001813,Male,No,0,Graduate,Yes,6050,4333,120,180,1,Urban,N
248
+ LP001814,Male,Yes,2,Graduate,No,9703,0,112,360,1,Urban,Y
249
+ LP001819,Male,Yes,1,Not Graduate,No,6608,0,137,180,1,Urban,Y
250
+ LP001824,Male,Yes,1,Graduate,No,2882,1843,123,480,1,Semiurban,Y
251
+ LP001825,Male,Yes,0,Graduate,No,1809,1868,90,360,1,Urban,Y
252
+ LP001835,Male,Yes,0,Not Graduate,No,1668,3890,201,360,0,Semiurban,N
253
+ LP001836,Female,No,2,Graduate,No,3427,0,138,360,1,Urban,N
254
+ LP001841,Male,No,0,Not Graduate,Yes,2583,2167,104,360,1,Rural,Y
255
+ LP001843,Male,Yes,1,Not Graduate,No,2661,7101,279,180,1,Semiurban,Y
256
+ LP001844,Male,No,0,Graduate,Yes,16250,0,192,360,0,Urban,N
257
+ LP001846,Female,No,3+,Graduate,No,3083,0,255,360,1,Rural,Y
258
+ LP001849,Male,No,0,Not Graduate,No,6045,0,115,360,0,Rural,N
259
+ LP001854,Male,Yes,3+,Graduate,No,5250,0,94,360,1,Urban,N
260
+ LP001859,Male,Yes,0,Graduate,No,14683,2100,304,360,1,Rural,N
261
+ LP001864,Male,Yes,3+,Not Graduate,No,4931,0,128,360,,Semiurban,N
262
+ LP001865,Male,Yes,1,Graduate,No,6083,4250,330,360,,Urban,Y
263
+ LP001868,Male,No,0,Graduate,No,2060,2209,134,360,1,Semiurban,Y
264
+ LP001870,Female,No,1,Graduate,No,3481,0,155,36,1,Semiurban,N
265
+ LP001871,Female,No,0,Graduate,No,7200,0,120,360,1,Rural,Y
266
+ LP001872,Male,No,0,Graduate,Yes,5166,0,128,360,1,Semiurban,Y
267
+ LP001875,Male,No,0,Graduate,No,4095,3447,151,360,1,Rural,Y
268
+ LP001877,Male,Yes,2,Graduate,No,4708,1387,150,360,1,Semiurban,Y
269
+ LP001882,Male,Yes,3+,Graduate,No,4333,1811,160,360,0,Urban,Y
270
+ LP001883,Female,No,0,Graduate,,3418,0,135,360,1,Rural,N
271
+ LP001884,Female,No,1,Graduate,No,2876,1560,90,360,1,Urban,Y
272
+ LP001888,Female,No,0,Graduate,No,3237,0,30,360,1,Urban,Y
273
+ LP001891,Male,Yes,0,Graduate,No,11146,0,136,360,1,Urban,Y
274
+ LP001892,Male,No,0,Graduate,No,2833,1857,126,360,1,Rural,Y
275
+ LP001894,Male,Yes,0,Graduate,No,2620,2223,150,360,1,Semiurban,Y
276
+ LP001896,Male,Yes,2,Graduate,No,3900,0,90,360,1,Semiurban,Y
277
+ LP001900,Male,Yes,1,Graduate,No,2750,1842,115,360,1,Semiurban,Y
278
+ LP001903,Male,Yes,0,Graduate,No,3993,3274,207,360,1,Semiurban,Y
279
+ LP001904,Male,Yes,0,Graduate,No,3103,1300,80,360,1,Urban,Y
280
+ LP001907,Male,Yes,0,Graduate,No,14583,0,436,360,1,Semiurban,Y
281
+ LP001908,Female,Yes,0,Not Graduate,No,4100,0,124,360,,Rural,Y
282
+ LP001910,Male,No,1,Not Graduate,Yes,4053,2426,158,360,0,Urban,N
283
+ LP001914,Male,Yes,0,Graduate,No,3927,800,112,360,1,Semiurban,Y
284
+ LP001915,Male,Yes,2,Graduate,No,2301,985.7999878,78,180,1,Urban,Y
285
+ LP001917,Female,No,0,Graduate,No,1811,1666,54,360,1,Urban,Y
286
+ LP001922,Male,Yes,0,Graduate,No,20667,0,,360,1,Rural,N
287
+ LP001924,Male,No,0,Graduate,No,3158,3053,89,360,1,Rural,Y
288
+ LP001925,Female,No,0,Graduate,Yes,2600,1717,99,300,1,Semiurban,N
289
+ LP001926,Male,Yes,0,Graduate,No,3704,2000,120,360,1,Rural,Y
290
+ LP001931,Female,No,0,Graduate,No,4124,0,115,360,1,Semiurban,Y
291
+ LP001935,Male,No,0,Graduate,No,9508,0,187,360,1,Rural,Y
292
+ LP001936,Male,Yes,0,Graduate,No,3075,2416,139,360,1,Rural,Y
293
+ LP001938,Male,Yes,2,Graduate,No,4400,0,127,360,0,Semiurban,N
294
+ LP001940,Male,Yes,2,Graduate,No,3153,1560,134,360,1,Urban,Y
295
+ LP001945,Female,No,,Graduate,No,5417,0,143,480,0,Urban,N
296
+ LP001947,Male,Yes,0,Graduate,No,2383,3334,172,360,1,Semiurban,Y
297
+ LP001949,Male,Yes,3+,Graduate,,4416,1250,110,360,1,Urban,Y
298
+ LP001953,Male,Yes,1,Graduate,No,6875,0,200,360,1,Semiurban,Y
299
+ LP001954,Female,Yes,1,Graduate,No,4666,0,135,360,1,Urban,Y
300
+ LP001955,Female,No,0,Graduate,No,5000,2541,151,480,1,Rural,N
301
+ LP001963,Male,Yes,1,Graduate,No,2014,2925,113,360,1,Urban,N
302
+ LP001964,Male,Yes,0,Not Graduate,No,1800,2934,93,360,0,Urban,N
303
+ LP001972,Male,Yes,,Not Graduate,No,2875,1750,105,360,1,Semiurban,Y
304
+ LP001974,Female,No,0,Graduate,No,5000,0,132,360,1,Rural,Y
305
+ LP001977,Male,Yes,1,Graduate,No,1625,1803,96,360,1,Urban,Y
306
+ LP001978,Male,No,0,Graduate,No,4000,2500,140,360,1,Rural,Y
307
+ LP001990,Male,No,0,Not Graduate,No,2000,0,,360,1,Urban,N
308
+ LP001993,Female,No,0,Graduate,No,3762,1666,135,360,1,Rural,Y
309
+ LP001994,Female,No,0,Graduate,No,2400,1863,104,360,0,Urban,N
310
+ LP001996,Male,No,0,Graduate,No,20233,0,480,360,1,Rural,N
311
+ LP001998,Male,Yes,2,Not Graduate,No,7667,0,185,360,,Rural,Y
312
+ LP002002,Female,No,0,Graduate,No,2917,0,84,360,1,Semiurban,Y
313
+ LP002004,Male,No,0,Not Graduate,No,2927,2405,111,360,1,Semiurban,Y
314
+ LP002006,Female,No,0,Graduate,No,2507,0,56,360,1,Rural,Y
315
+ LP002008,Male,Yes,2,Graduate,Yes,5746,0,144,84,,Rural,Y
316
+ LP002024,,Yes,0,Graduate,No,2473,1843,159,360,1,Rural,N
317
+ LP002031,Male,Yes,1,Not Graduate,No,3399,1640,111,180,1,Urban,Y
318
+ LP002035,Male,Yes,2,Graduate,No,3717,0,120,360,1,Semiurban,Y
319
+ LP002036,Male,Yes,0,Graduate,No,2058,2134,88,360,,Urban,Y
320
+ LP002043,Female,No,1,Graduate,No,3541,0,112,360,,Semiurban,Y
321
+ LP002050,Male,Yes,1,Graduate,Yes,10000,0,155,360,1,Rural,N
322
+ LP002051,Male,Yes,0,Graduate,No,2400,2167,115,360,1,Semiurban,Y
323
+ LP002053,Male,Yes,3+,Graduate,No,4342,189,124,360,1,Semiurban,Y
324
+ LP002054,Male,Yes,2,Not Graduate,No,3601,1590,,360,1,Rural,Y
325
+ LP002055,Female,No,0,Graduate,No,3166,2985,132,360,,Rural,Y
326
+ LP002065,Male,Yes,3+,Graduate,No,15000,0,300,360,1,Rural,Y
327
+ LP002067,Male,Yes,1,Graduate,Yes,8666,4983,376,360,0,Rural,N
328
+ LP002068,Male,No,0,Graduate,No,4917,0,130,360,0,Rural,Y
329
+ LP002082,Male,Yes,0,Graduate,Yes,5818,2160,184,360,1,Semiurban,Y
330
+ LP002086,Female,Yes,0,Graduate,No,4333,2451,110,360,1,Urban,N
331
+ LP002087,Female,No,0,Graduate,No,2500,0,67,360,1,Urban,Y
332
+ LP002097,Male,No,1,Graduate,No,4384,1793,117,360,1,Urban,Y
333
+ LP002098,Male,No,0,Graduate,No,2935,0,98,360,1,Semiurban,Y
334
+ LP002100,Male,No,,Graduate,No,2833,0,71,360,1,Urban,Y
335
+ LP002101,Male,Yes,0,Graduate,,63337,0,490,180,1,Urban,Y
336
+ LP002103,,Yes,1,Graduate,Yes,9833,1833,182,180,1,Urban,Y
337
+ LP002106,Male,Yes,,Graduate,Yes,5503,4490,70,,1,Semiurban,Y
338
+ LP002110,Male,Yes,1,Graduate,,5250,688,160,360,1,Rural,Y
339
+ LP002112,Male,Yes,2,Graduate,Yes,2500,4600,176,360,1,Rural,Y
340
+ LP002113,Female,No,3+,Not Graduate,No,1830,0,,360,0,Urban,N
341
+ LP002114,Female,No,0,Graduate,No,4160,0,71,360,1,Semiurban,Y
342
+ LP002115,Male,Yes,3+,Not Graduate,No,2647,1587,173,360,1,Rural,N
343
+ LP002116,Female,No,0,Graduate,No,2378,0,46,360,1,Rural,N
344
+ LP002119,Male,Yes,1,Not Graduate,No,4554,1229,158,360,1,Urban,Y
345
+ LP002126,Male,Yes,3+,Not Graduate,No,3173,0,74,360,1,Semiurban,Y
346
+ LP002128,Male,Yes,2,Graduate,,2583,2330,125,360,1,Rural,Y
347
+ LP002129,Male,Yes,0,Graduate,No,2499,2458,160,360,1,Semiurban,Y
348
+ LP002130,Male,Yes,,Not Graduate,No,3523,3230,152,360,0,Rural,N
349
+ LP002131,Male,Yes,2,Not Graduate,No,3083,2168,126,360,1,Urban,Y
350
+ LP002137,Male,Yes,0,Graduate,No,6333,4583,259,360,,Semiurban,Y
351
+ LP002138,Male,Yes,0,Graduate,No,2625,6250,187,360,1,Rural,Y
352
+ LP002139,Male,Yes,0,Graduate,No,9083,0,228,360,1,Semiurban,Y
353
+ LP002140,Male,No,0,Graduate,No,8750,4167,308,360,1,Rural,N
354
+ LP002141,Male,Yes,3+,Graduate,No,2666,2083,95,360,1,Rural,Y
355
+ LP002142,Female,Yes,0,Graduate,Yes,5500,0,105,360,0,Rural,N
356
+ LP002143,Female,Yes,0,Graduate,No,2423,505,130,360,1,Semiurban,Y
357
+ LP002144,Female,No,,Graduate,No,3813,0,116,180,1,Urban,Y
358
+ LP002149,Male,Yes,2,Graduate,No,8333,3167,165,360,1,Rural,Y
359
+ LP002151,Male,Yes,1,Graduate,No,3875,0,67,360,1,Urban,N
360
+ LP002158,Male,Yes,0,Not Graduate,No,3000,1666,100,480,0,Urban,N
361
+ LP002160,Male,Yes,3+,Graduate,No,5167,3167,200,360,1,Semiurban,Y
362
+ LP002161,Female,No,1,Graduate,No,4723,0,81,360,1,Semiurban,N
363
+ LP002170,Male,Yes,2,Graduate,No,5000,3667,236,360,1,Semiurban,Y
364
+ LP002175,Male,Yes,0,Graduate,No,4750,2333,130,360,1,Urban,Y
365
+ LP002178,Male,Yes,0,Graduate,No,3013,3033,95,300,,Urban,Y
366
+ LP002180,Male,No,0,Graduate,Yes,6822,0,141,360,1,Rural,Y
367
+ LP002181,Male,No,0,Not Graduate,No,6216,0,133,360,1,Rural,N
368
+ LP002187,Male,No,0,Graduate,No,2500,0,96,480,1,Semiurban,N
369
+ LP002188,Male,No,0,Graduate,No,5124,0,124,,0,Rural,N
370
+ LP002190,Male,Yes,1,Graduate,No,6325,0,175,360,1,Semiurban,Y
371
+ LP002191,Male,Yes,0,Graduate,No,19730,5266,570,360,1,Rural,N
372
+ LP002194,Female,No,0,Graduate,Yes,15759,0,55,360,1,Semiurban,Y
373
+ LP002197,Male,Yes,2,Graduate,No,5185,0,155,360,1,Semiurban,Y
374
+ LP002201,Male,Yes,2,Graduate,Yes,9323,7873,380,300,1,Rural,Y
375
+ LP002205,Male,No,1,Graduate,No,3062,1987,111,180,0,Urban,N
376
+ LP002209,Female,No,0,Graduate,,2764,1459,110,360,1,Urban,Y
377
+ LP002211,Male,Yes,0,Graduate,No,4817,923,120,180,1,Urban,Y
378
+ LP002219,Male,Yes,3+,Graduate,No,8750,4996,130,360,1,Rural,Y
379
+ LP002223,Male,Yes,0,Graduate,No,4310,0,130,360,,Semiurban,Y
380
+ LP002224,Male,No,0,Graduate,No,3069,0,71,480,1,Urban,N
381
+ LP002225,Male,Yes,2,Graduate,No,5391,0,130,360,1,Urban,Y
382
+ LP002226,Male,Yes,0,Graduate,,3333,2500,128,360,1,Semiurban,Y
383
+ LP002229,Male,No,0,Graduate,No,5941,4232,296,360,1,Semiurban,Y
384
+ LP002231,Female,No,0,Graduate,No,6000,0,156,360,1,Urban,Y
385
+ LP002234,Male,No,0,Graduate,Yes,7167,0,128,360,1,Urban,Y
386
+ LP002236,Male,Yes,2,Graduate,No,4566,0,100,360,1,Urban,N
387
+ LP002237,Male,No,1,Graduate,,3667,0,113,180,1,Urban,Y
388
+ LP002239,Male,No,0,Not Graduate,No,2346,1600,132,360,1,Semiurban,Y
389
+ LP002243,Male,Yes,0,Not Graduate,No,3010,3136,,360,0,Urban,N
390
+ LP002244,Male,Yes,0,Graduate,No,2333,2417,136,360,1,Urban,Y
391
+ LP002250,Male,Yes,0,Graduate,No,5488,0,125,360,1,Rural,Y
392
+ LP002255,Male,No,3+,Graduate,No,9167,0,185,360,1,Rural,Y
393
+ LP002262,Male,Yes,3+,Graduate,No,9504,0,275,360,1,Rural,Y
394
+ LP002263,Male,Yes,0,Graduate,No,2583,2115,120,360,,Urban,Y
395
+ LP002265,Male,Yes,2,Not Graduate,No,1993,1625,113,180,1,Semiurban,Y
396
+ LP002266,Male,Yes,2,Graduate,No,3100,1400,113,360,1,Urban,Y
397
+ LP002272,Male,Yes,2,Graduate,No,3276,484,135,360,,Semiurban,Y
398
+ LP002277,Female,No,0,Graduate,No,3180,0,71,360,0,Urban,N
399
+ LP002281,Male,Yes,0,Graduate,No,3033,1459,95,360,1,Urban,Y
400
+ LP002284,Male,No,0,Not Graduate,No,3902,1666,109,360,1,Rural,Y
401
+ LP002287,Female,No,0,Graduate,No,1500,1800,103,360,0,Semiurban,N
402
+ LP002288,Male,Yes,2,Not Graduate,No,2889,0,45,180,0,Urban,N
403
+ LP002296,Male,No,0,Not Graduate,No,2755,0,65,300,1,Rural,N
404
+ LP002297,Male,No,0,Graduate,No,2500,20000,103,360,1,Semiurban,Y
405
+ LP002300,Female,No,0,Not Graduate,No,1963,0,53,360,1,Semiurban,Y
406
+ LP002301,Female,No,0,Graduate,Yes,7441,0,194,360,1,Rural,N
407
+ LP002305,Female,No,0,Graduate,No,4547,0,115,360,1,Semiurban,Y
408
+ LP002308,Male,Yes,0,Not Graduate,No,2167,2400,115,360,1,Urban,Y
409
+ LP002314,Female,No,0,Not Graduate,No,2213,0,66,360,1,Rural,Y
410
+ LP002315,Male,Yes,1,Graduate,No,8300,0,152,300,0,Semiurban,N
411
+ LP002317,Male,Yes,3+,Graduate,No,81000,0,360,360,0,Rural,N
412
+ LP002318,Female,No,1,Not Graduate,Yes,3867,0,62,360,1,Semiurban,N
413
+ LP002319,Male,Yes,0,Graduate,,6256,0,160,360,,Urban,Y
414
+ LP002328,Male,Yes,0,Not Graduate,No,6096,0,218,360,0,Rural,N
415
+ LP002332,Male,Yes,0,Not Graduate,No,2253,2033,110,360,1,Rural,Y
416
+ LP002335,Female,Yes,0,Not Graduate,No,2149,3237,178,360,0,Semiurban,N
417
+ LP002337,Female,No,0,Graduate,No,2995,0,60,360,1,Urban,Y
418
+ LP002341,Female,No,1,Graduate,No,2600,0,160,360,1,Urban,N
419
+ LP002342,Male,Yes,2,Graduate,Yes,1600,20000,239,360,1,Urban,N
420
+ LP002345,Male,Yes,0,Graduate,No,1025,2773,112,360,1,Rural,Y
421
+ LP002347,Male,Yes,0,Graduate,No,3246,1417,138,360,1,Semiurban,Y
422
+ LP002348,Male,Yes,0,Graduate,No,5829,0,138,360,1,Rural,Y
423
+ LP002357,Female,No,0,Not Graduate,No,2720,0,80,,0,Urban,N
424
+ LP002361,Male,Yes,0,Graduate,No,1820,1719,100,360,1,Urban,Y
425
+ LP002362,Male,Yes,1,Graduate,No,7250,1667,110,,0,Urban,N
426
+ LP002364,Male,Yes,0,Graduate,No,14880,0,96,360,1,Semiurban,Y
427
+ LP002366,Male,Yes,0,Graduate,No,2666,4300,121,360,1,Rural,Y
428
+ LP002367,Female,No,1,Not Graduate,No,4606,0,81,360,1,Rural,N
429
+ LP002368,Male,Yes,2,Graduate,No,5935,0,133,360,1,Semiurban,Y
430
+ LP002369,Male,Yes,0,Graduate,No,2920,16.12000084,87,360,1,Rural,Y
431
+ LP002370,Male,No,0,Not Graduate,No,2717,0,60,180,1,Urban,Y
432
+ LP002377,Female,No,1,Graduate,Yes,8624,0,150,360,1,Semiurban,Y
433
+ LP002379,Male,No,0,Graduate,No,6500,0,105,360,0,Rural,N
434
+ LP002386,Male,No,0,Graduate,,12876,0,405,360,1,Semiurban,Y
435
+ LP002387,Male,Yes,0,Graduate,No,2425,2340,143,360,1,Semiurban,Y
436
+ LP002390,Male,No,0,Graduate,No,3750,0,100,360,1,Urban,Y
437
+ LP002393,Female,,,Graduate,No,10047,0,,240,1,Semiurban,Y
438
+ LP002398,Male,No,0,Graduate,No,1926,1851,50,360,1,Semiurban,Y
439
+ LP002401,Male,Yes,0,Graduate,No,2213,1125,,360,1,Urban,Y
440
+ LP002403,Male,No,0,Graduate,Yes,10416,0,187,360,0,Urban,N
441
+ LP002407,Female,Yes,0,Not Graduate,Yes,7142,0,138,360,1,Rural,Y
442
+ LP002408,Male,No,0,Graduate,No,3660,5064,187,360,1,Semiurban,Y
443
+ LP002409,Male,Yes,0,Graduate,No,7901,1833,180,360,1,Rural,Y
444
+ LP002418,Male,No,3+,Not Graduate,No,4707,1993,148,360,1,Semiurban,Y
445
+ LP002422,Male,No,1,Graduate,No,37719,0,152,360,1,Semiurban,Y
446
+ LP002424,Male,Yes,0,Graduate,No,7333,8333,175,300,,Rural,Y
447
+ LP002429,Male,Yes,1,Graduate,Yes,3466,1210,130,360,1,Rural,Y
448
+ LP002434,Male,Yes,2,Not Graduate,No,4652,0,110,360,1,Rural,Y
449
+ LP002435,Male,Yes,0,Graduate,,3539,1376,55,360,1,Rural,N
450
+ LP002443,Male,Yes,2,Graduate,No,3340,1710,150,360,0,Rural,N
451
+ LP002444,Male,No,1,Not Graduate,Yes,2769,1542,190,360,,Semiurban,N
452
+ LP002446,Male,Yes,2,Not Graduate,No,2309,1255,125,360,0,Rural,N
453
+ LP002447,Male,Yes,2,Not Graduate,No,1958,1456,60,300,,Urban,Y
454
+ LP002448,Male,Yes,0,Graduate,No,3948,1733,149,360,0,Rural,N
455
+ LP002449,Male,Yes,0,Graduate,No,2483,2466,90,180,0,Rural,Y
456
+ LP002453,Male,No,0,Graduate,Yes,7085,0,84,360,1,Semiurban,Y
457
+ LP002455,Male,Yes,2,Graduate,No,3859,0,96,360,1,Semiurban,Y
458
+ LP002459,Male,Yes,0,Graduate,No,4301,0,118,360,1,Urban,Y
459
+ LP002467,Male,Yes,0,Graduate,No,3708,2569,173,360,1,Urban,N
460
+ LP002472,Male,No,2,Graduate,No,4354,0,136,360,1,Rural,Y
461
+ LP002473,Male,Yes,0,Graduate,No,8334,0,160,360,1,Semiurban,N
462
+ LP002478,,Yes,0,Graduate,Yes,2083,4083,160,360,,Semiurban,Y
463
+ LP002484,Male,Yes,3+,Graduate,No,7740,0,128,180,1,Urban,Y
464
+ LP002487,Male,Yes,0,Graduate,No,3015,2188,153,360,1,Rural,Y
465
+ LP002489,Female,No,1,Not Graduate,,5191,0,132,360,1,Semiurban,Y
466
+ LP002493,Male,No,0,Graduate,No,4166,0,98,360,0,Semiurban,N
467
+ LP002494,Male,No,0,Graduate,No,6000,0,140,360,1,Rural,Y
468
+ LP002500,Male,Yes,3+,Not Graduate,No,2947,1664,70,180,0,Urban,N
469
+ LP002501,,Yes,0,Graduate,No,16692,0,110,360,1,Semiurban,Y
470
+ LP002502,Female,Yes,2,Not Graduate,,210,2917,98,360,1,Semiurban,Y
471
+ LP002505,Male,Yes,0,Graduate,No,4333,2451,110,360,1,Urban,N
472
+ LP002515,Male,Yes,1,Graduate,Yes,3450,2079,162,360,1,Semiurban,Y
473
+ LP002517,Male,Yes,1,Not Graduate,No,2653,1500,113,180,0,Rural,N
474
+ LP002519,Male,Yes,3+,Graduate,No,4691,0,100,360,1,Semiurban,Y
475
+ LP002522,Female,No,0,Graduate,Yes,2500,0,93,360,,Urban,Y
476
+ LP002524,Male,No,2,Graduate,No,5532,4648,162,360,1,Rural,Y
477
+ LP002527,Male,Yes,2,Graduate,Yes,16525,1014,150,360,1,Rural,Y
478
+ LP002529,Male,Yes,2,Graduate,No,6700,1750,230,300,1,Semiurban,Y
479
+ LP002530,,Yes,2,Graduate,No,2873,1872,132,360,0,Semiurban,N
480
+ LP002531,Male,Yes,1,Graduate,Yes,16667,2250,86,360,1,Semiurban,Y
481
+ LP002533,Male,Yes,2,Graduate,No,2947,1603,,360,1,Urban,N
482
+ LP002534,Female,No,0,Not Graduate,No,4350,0,154,360,1,Rural,Y
483
+ LP002536,Male,Yes,3+,Not Graduate,No,3095,0,113,360,1,Rural,Y
484
+ LP002537,Male,Yes,0,Graduate,No,2083,3150,128,360,1,Semiurban,Y
485
+ LP002541,Male,Yes,0,Graduate,No,10833,0,234,360,1,Semiurban,Y
486
+ LP002543,Male,Yes,2,Graduate,No,8333,0,246,360,1,Semiurban,Y
487
+ LP002544,Male,Yes,1,Not Graduate,No,1958,2436,131,360,1,Rural,Y
488
+ LP002545,Male,No,2,Graduate,No,3547,0,80,360,0,Rural,N
489
+ LP002547,Male,Yes,1,Graduate,No,18333,0,500,360,1,Urban,N
490
+ LP002555,Male,Yes,2,Graduate,Yes,4583,2083,160,360,1,Semiurban,Y
491
+ LP002556,Male,No,0,Graduate,No,2435,0,75,360,1,Urban,N
492
+ LP002560,Male,No,0,Not Graduate,No,2699,2785,96,360,,Semiurban,Y
493
+ LP002562,Male,Yes,1,Not Graduate,No,5333,1131,186,360,,Urban,Y
494
+ LP002571,Male,No,0,Not Graduate,No,3691,0,110,360,1,Rural,Y
495
+ LP002582,Female,No,0,Not Graduate,Yes,17263,0,225,360,1,Semiurban,Y
496
+ LP002585,Male,Yes,0,Graduate,No,3597,2157,119,360,0,Rural,N
497
+ LP002586,Female,Yes,1,Graduate,No,3326,913,105,84,1,Semiurban,Y
498
+ LP002587,Male,Yes,0,Not Graduate,No,2600,1700,107,360,1,Rural,Y
499
+ LP002588,Male,Yes,0,Graduate,No,4625,2857,111,12,,Urban,Y
500
+ LP002600,Male,Yes,1,Graduate,Yes,2895,0,95,360,1,Semiurban,Y
501
+ LP002602,Male,No,0,Graduate,No,6283,4416,209,360,0,Rural,N
502
+ LP002603,Female,No,0,Graduate,No,645,3683,113,480,1,Rural,Y
503
+ LP002606,Female,No,0,Graduate,No,3159,0,100,360,1,Semiurban,Y
504
+ LP002615,Male,Yes,2,Graduate,No,4865,5624,208,360,1,Semiurban,Y
505
+ LP002618,Male,Yes,1,Not Graduate,No,4050,5302,138,360,,Rural,N
506
+ LP002619,Male,Yes,0,Not Graduate,No,3814,1483,124,300,1,Semiurban,Y
507
+ LP002622,Male,Yes,2,Graduate,No,3510,4416,243,360,1,Rural,Y
508
+ LP002624,Male,Yes,0,Graduate,No,20833,6667,480,360,,Urban,Y
509
+ LP002625,,No,0,Graduate,No,3583,0,96,360,1,Urban,N
510
+ LP002626,Male,Yes,0,Graduate,Yes,2479,3013,188,360,1,Urban,Y
511
+ LP002634,Female,No,1,Graduate,No,13262,0,40,360,1,Urban,Y
512
+ LP002637,Male,No,0,Not Graduate,No,3598,1287,100,360,1,Rural,N
513
+ LP002640,Male,Yes,1,Graduate,No,6065,2004,250,360,1,Semiurban,Y
514
+ LP002643,Male,Yes,2,Graduate,No,3283,2035,148,360,1,Urban,Y
515
+ LP002648,Male,Yes,0,Graduate,No,2130,6666,70,180,1,Semiurban,N
516
+ LP002652,Male,No,0,Graduate,No,5815,3666,311,360,1,Rural,N
517
+ LP002659,Male,Yes,3+,Graduate,No,3466,3428,150,360,1,Rural,Y
518
+ LP002670,Female,Yes,2,Graduate,No,2031,1632,113,480,1,Semiurban,Y
519
+ LP002682,Male,Yes,,Not Graduate,No,3074,1800,123,360,0,Semiurban,N
520
+ LP002683,Male,No,0,Graduate,No,4683,1915,185,360,1,Semiurban,N
521
+ LP002684,Female,No,0,Not Graduate,No,3400,0,95,360,1,Rural,N
522
+ LP002689,Male,Yes,2,Not Graduate,No,2192,1742,45,360,1,Semiurban,Y
523
+ LP002690,Male,No,0,Graduate,No,2500,0,55,360,1,Semiurban,Y
524
+ LP002692,Male,Yes,3+,Graduate,Yes,5677,1424,100,360,1,Rural,Y
525
+ LP002693,Male,Yes,2,Graduate,Yes,7948,7166,480,360,1,Rural,Y
526
+ LP002697,Male,No,0,Graduate,No,4680,2087,,360,1,Semiurban,N
527
+ LP002699,Male,Yes,2,Graduate,Yes,17500,0,400,360,1,Rural,Y
528
+ LP002705,Male,Yes,0,Graduate,No,3775,0,110,360,1,Semiurban,Y
529
+ LP002706,Male,Yes,1,Not Graduate,No,5285,1430,161,360,0,Semiurban,Y
530
+ LP002714,Male,No,1,Not Graduate,No,2679,1302,94,360,1,Semiurban,Y
531
+ LP002716,Male,No,0,Not Graduate,No,6783,0,130,360,1,Semiurban,Y
532
+ LP002717,Male,Yes,0,Graduate,No,1025,5500,216,360,,Rural,Y
533
+ LP002720,Male,Yes,3+,Graduate,No,4281,0,100,360,1,Urban,Y
534
+ LP002723,Male,No,2,Graduate,No,3588,0,110,360,0,Rural,N
535
+ LP002729,Male,No,1,Graduate,No,11250,0,196,360,,Semiurban,N
536
+ LP002731,Female,No,0,Not Graduate,Yes,18165,0,125,360,1,Urban,Y
537
+ LP002732,Male,No,0,Not Graduate,,2550,2042,126,360,1,Rural,Y
538
+ LP002734,Male,Yes,0,Graduate,No,6133,3906,324,360,1,Urban,Y
539
+ LP002738,Male,No,2,Graduate,No,3617,0,107,360,1,Semiurban,Y
540
+ LP002739,Male,Yes,0,Not Graduate,No,2917,536,66,360,1,Rural,N
541
+ LP002740,Male,Yes,3+,Graduate,No,6417,0,157,180,1,Rural,Y
542
+ LP002741,Female,Yes,1,Graduate,No,4608,2845,140,180,1,Semiurban,Y
543
+ LP002743,Female,No,0,Graduate,No,2138,0,99,360,0,Semiurban,N
544
+ LP002753,Female,No,1,Graduate,,3652,0,95,360,1,Semiurban,Y
545
+ LP002755,Male,Yes,1,Not Graduate,No,2239,2524,128,360,1,Urban,Y
546
+ LP002757,Female,Yes,0,Not Graduate,No,3017,663,102,360,,Semiurban,Y
547
+ LP002767,Male,Yes,0,Graduate,No,2768,1950,155,360,1,Rural,Y
548
+ LP002768,Male,No,0,Not Graduate,No,3358,0,80,36,1,Semiurban,N
549
+ LP002772,Male,No,0,Graduate,No,2526,1783,145,360,1,Rural,Y
550
+ LP002776,Female,No,0,Graduate,No,5000,0,103,360,0,Semiurban,N
551
+ LP002777,Male,Yes,0,Graduate,No,2785,2016,110,360,1,Rural,Y
552
+ LP002778,Male,Yes,2,Graduate,Yes,6633,0,,360,0,Rural,N
553
+ LP002784,Male,Yes,1,Not Graduate,No,2492,2375,,360,1,Rural,Y
554
+ LP002785,Male,Yes,1,Graduate,No,3333,3250,158,360,1,Urban,Y
555
+ LP002788,Male,Yes,0,Not Graduate,No,2454,2333,181,360,0,Urban,N
556
+ LP002789,Male,Yes,0,Graduate,No,3593,4266,132,180,0,Rural,N
557
+ LP002792,Male,Yes,1,Graduate,No,5468,1032,26,360,1,Semiurban,Y
558
+ LP002794,Female,No,0,Graduate,No,2667,1625,84,360,,Urban,Y
559
+ LP002795,Male,Yes,3+,Graduate,Yes,10139,0,260,360,1,Semiurban,Y
560
+ LP002798,Male,Yes,0,Graduate,No,3887,2669,162,360,1,Semiurban,Y
561
+ LP002804,Female,Yes,0,Graduate,No,4180,2306,182,360,1,Semiurban,Y
562
+ LP002807,Male,Yes,2,Not Graduate,No,3675,242,108,360,1,Semiurban,Y
563
+ LP002813,Female,Yes,1,Graduate,Yes,19484,0,600,360,1,Semiurban,Y
564
+ LP002820,Male,Yes,0,Graduate,No,5923,2054,211,360,1,Rural,Y
565
+ LP002821,Male,No,0,Not Graduate,Yes,5800,0,132,360,1,Semiurban,Y
566
+ LP002832,Male,Yes,2,Graduate,No,8799,0,258,360,0,Urban,N
567
+ LP002833,Male,Yes,0,Not Graduate,No,4467,0,120,360,,Rural,Y
568
+ LP002836,Male,No,0,Graduate,No,3333,0,70,360,1,Urban,Y
569
+ LP002837,Male,Yes,3+,Graduate,No,3400,2500,123,360,0,Rural,N
570
+ LP002840,Female,No,0,Graduate,No,2378,0,9,360,1,Urban,N
571
+ LP002841,Male,Yes,0,Graduate,No,3166,2064,104,360,0,Urban,N
572
+ LP002842,Male,Yes,1,Graduate,No,3417,1750,186,360,1,Urban,Y
573
+ LP002847,Male,Yes,,Graduate,No,5116,1451,165,360,0,Urban,N
574
+ LP002855,Male,Yes,2,Graduate,No,16666,0,275,360,1,Urban,Y
575
+ LP002862,Male,Yes,2,Not Graduate,No,6125,1625,187,480,1,Semiurban,N
576
+ LP002863,Male,Yes,3+,Graduate,No,6406,0,150,360,1,Semiurban,N
577
+ LP002868,Male,Yes,2,Graduate,No,3159,461,108,84,1,Urban,Y
578
+ LP002872,,Yes,0,Graduate,No,3087,2210,136,360,0,Semiurban,N
579
+ LP002874,Male,No,0,Graduate,No,3229,2739,110,360,1,Urban,Y
580
+ LP002877,Male,Yes,1,Graduate,No,1782,2232,107,360,1,Rural,Y
581
+ LP002888,Male,No,0,Graduate,,3182,2917,161,360,1,Urban,Y
582
+ LP002892,Male,Yes,2,Graduate,No,6540,0,205,360,1,Semiurban,Y
583
+ LP002893,Male,No,0,Graduate,No,1836,33837,90,360,1,Urban,N
584
+ LP002894,Female,Yes,0,Graduate,No,3166,0,36,360,1,Semiurban,Y
585
+ LP002898,Male,Yes,1,Graduate,No,1880,0,61,360,,Rural,N
586
+ LP002911,Male,Yes,1,Graduate,No,2787,1917,146,360,0,Rural,N
587
+ LP002912,Male,Yes,1,Graduate,No,4283,3000,172,84,1,Rural,N
588
+ LP002916,Male,Yes,0,Graduate,No,2297,1522,104,360,1,Urban,Y
589
+ LP002917,Female,No,0,Not Graduate,No,2165,0,70,360,1,Semiurban,Y
590
+ LP002925,,No,0,Graduate,No,4750,0,94,360,1,Semiurban,Y
591
+ LP002926,Male,Yes,2,Graduate,Yes,2726,0,106,360,0,Semiurban,N
592
+ LP002928,Male,Yes,0,Graduate,No,3000,3416,56,180,1,Semiurban,Y
593
+ LP002931,Male,Yes,2,Graduate,Yes,6000,0,205,240,1,Semiurban,N
594
+ LP002933,,No,3+,Graduate,Yes,9357,0,292,360,1,Semiurban,Y
595
+ LP002936,Male,Yes,0,Graduate,No,3859,3300,142,180,1,Rural,Y
596
+ LP002938,Male,Yes,0,Graduate,Yes,16120,0,260,360,1,Urban,Y
597
+ LP002940,Male,No,0,Not Graduate,No,3833,0,110,360,1,Rural,Y
598
+ LP002941,Male,Yes,2,Not Graduate,Yes,6383,1000,187,360,1,Rural,N
599
+ LP002943,Male,No,,Graduate,No,2987,0,88,360,0,Semiurban,N
600
+ LP002945,Male,Yes,0,Graduate,Yes,9963,0,180,360,1,Rural,Y
601
+ LP002948,Male,Yes,2,Graduate,No,5780,0,192,360,1,Urban,Y
602
+ LP002949,Female,No,3+,Graduate,,416,41667,350,180,,Urban,N
603
+ LP002950,Male,Yes,0,Not Graduate,,2894,2792,155,360,1,Rural,Y
604
+ LP002953,Male,Yes,3+,Graduate,No,5703,0,128,360,1,Urban,Y
605
+ LP002958,Male,No,0,Graduate,No,3676,4301,172,360,1,Rural,Y
606
+ LP002959,Female,Yes,1,Graduate,No,12000,0,496,360,1,Semiurban,Y
607
+ LP002960,Male,Yes,0,Not Graduate,No,2400,3800,,180,1,Urban,N
608
+ LP002961,Male,Yes,1,Graduate,No,3400,2500,173,360,1,Semiurban,Y
609
+ LP002964,Male,Yes,2,Not Graduate,No,3987,1411,157,360,1,Rural,Y
610
+ LP002974,Male,Yes,0,Graduate,No,3232,1950,108,360,1,Rural,Y
611
+ LP002978,Female,No,0,Graduate,No,2900,0,71,360,1,Rural,Y
612
+ LP002979,Male,Yes,3+,Graduate,No,4106,0,40,180,1,Rural,Y
613
+ LP002983,Male,Yes,1,Graduate,No,8072,240,253,360,1,Urban,Y
614
+ LP002984,Male,Yes,2,Graduate,No,7583,0,187,360,1,Urban,Y
615
+ LP002990,Female,No,0,Graduate,Yes,4583,0,133,360,0,Semiurban,N
new_data/german-fewshot-2.csv ADDED
@@ -0,0 +1,151 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Unnamed: 0,gender,checking_status,duration,credit_history,purpose,credit_amount,savings_status,employment,installment_commitment,other_parties,residence_since,property_magnitude,age,other_payment_plans,housing,existing_credits,job,num_dependents,own_telephone,foreign_worker,class,great,list,text,html,latex,json,LIFT
2
+ 0,male,'<0',60,'delayed previously',business,6836,'<100','>=7',3,none,4,'no known property',63,none,own,2,skilled,1,yes,yes,bad,"gender is male, checking_status is '<0', duration is 60, credit_history is 'delayed previously', purpose is business, credit_amount is 6836, savings_status is '<100', employment is '>=7', installment_commitment is 3, other_parties is none, residence_since is 4, property_magnitude is 'no known property', age is 63, other_payment_plans is none, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : male
3
+ - checking_status : '<0'
4
+ - duration : 60
5
+ - credit_history : 'delayed previously'
6
+ - purpose : business
7
+ - credit_amount : 6836
8
+ - savings_status : '<100'
9
+ - employment : '>=7'
10
+ - installment_commitment : 3
11
+ - other_parties : none
12
+ - residence_since : 4
13
+ - property_magnitude : 'no known property'
14
+ - age : 63
15
+ - other_payment_plans : none
16
+ - housing : own
17
+ - existing_credits : 2
18
+ - job : skilled
19
+ - num_dependents : 1
20
+ - own_telephone : yes
21
+ - foreign_worker : yes",The gender is male. The checking_status is '<0'. The duration is 60. The credit_history is 'delayed previously'. The purpose is business. The credit_amount is 6836. The savings_status is '<100'. The employment is '>=7'. The installment_commitment is 3. The other_parties is none. The residence_since is 4. The property_magnitude is 'no known property'. The age is 63. The other_payment_plans is none. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
22
+ <thead>
23
+ <tr style=""text-align: right;"">
24
+ <th></th>
25
+ <th>gender</th>
26
+ <th>checking_status</th>
27
+ <th>duration</th>
28
+ <th>credit_history</th>
29
+ <th>purpose</th>
30
+ <th>credit_amount</th>
31
+ <th>savings_status</th>
32
+ <th>employment</th>
33
+ <th>installment_commitment</th>
34
+ <th>other_parties</th>
35
+ <th>residence_since</th>
36
+ <th>property_magnitude</th>
37
+ <th>age</th>
38
+ <th>other_payment_plans</th>
39
+ <th>housing</th>
40
+ <th>existing_credits</th>
41
+ <th>job</th>
42
+ <th>num_dependents</th>
43
+ <th>own_telephone</th>
44
+ <th>foreign_worker</th>
45
+ </tr>
46
+ </thead>
47
+ <tbody>
48
+ <tr>
49
+ <th>0</th>
50
+ <td>male</td>
51
+ <td>'&lt;0'</td>
52
+ <td>60</td>
53
+ <td>'delayed previously'</td>
54
+ <td>business</td>
55
+ <td>6836</td>
56
+ <td>'&lt;100'</td>
57
+ <td>'&gt;=7'</td>
58
+ <td>3</td>
59
+ <td>none</td>
60
+ <td>4</td>
61
+ <td>'no known property'</td>
62
+ <td>63</td>
63
+ <td>none</td>
64
+ <td>own</td>
65
+ <td>2</td>
66
+ <td>skilled</td>
67
+ <td>1</td>
68
+ <td>yes</td>
69
+ <td>yes</td>
70
+ </tr>
71
+ </tbody>
72
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
73
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
74
+ 0 & male & '<0' & 60 & 'delayed previously' & business & 6836 & '<100' & '>=7' & 3 & none & 4 & 'no known property' & 63 & none & own & 2 & skilled & 1 & yes & yes \\
75
+ \end{tabular}
76
+ ","{'age': 63, 'checking_status': ""'<0'"", 'credit_amount': 6836, 'credit_history': ""'delayed previously'"", 'duration': 60, 'employment': ""'>=7'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'own', 'installment_commitment': 3, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'yes', 'property_magnitude': ""'no known property'"", 'purpose': 'business', 'residence_since': 4, 'savings_status': ""'<100'""}",A 63-year-old male German Foreigner is applying for a loan of 6836 credits for 60 months for business purposes. He has a checking account with 0 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. He has delayed paying back credits received from this bank in the past. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 3%. He has no other installment plans and 2 credits at this bank. He is employed for more than seven years. He has lived in a self-owned house for 4 years. He owns no known property. He owns a telephone and has 1 person that he is liable to provide maintenance for.
77
+ 3,female,'no checking',21,'no credits/all paid','new car',5003,'no known savings','1<=X<4',1,none,4,'life insurance',29,bank,own,2,skilled,1,yes,yes,bad,"gender is female, checking_status is 'no checking', duration is 21, credit_history is 'no credits/all paid', purpose is 'new car', credit_amount is 5003, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 1, other_parties is none, residence_since is 4, property_magnitude is 'life insurance', age is 29, other_payment_plans is bank, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : female
78
+ - checking_status : 'no checking'
79
+ - duration : 21
80
+ - credit_history : 'no credits/all paid'
81
+ - purpose : 'new car'
82
+ - credit_amount : 5003
83
+ - savings_status : 'no known savings'
84
+ - employment : '1<=X<4'
85
+ - installment_commitment : 1
86
+ - other_parties : none
87
+ - residence_since : 4
88
+ - property_magnitude : 'life insurance'
89
+ - age : 29
90
+ - other_payment_plans : bank
91
+ - housing : own
92
+ - existing_credits : 2
93
+ - job : skilled
94
+ - num_dependents : 1
95
+ - own_telephone : yes
96
+ - foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 21. The credit_history is 'no credits/all paid'. The purpose is 'new car'. The credit_amount is 5003. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 1. The other_parties is none. The residence_since is 4. The property_magnitude is 'life insurance'. The age is 29. The other_payment_plans is bank. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
97
+ <thead>
98
+ <tr style=""text-align: right;"">
99
+ <th></th>
100
+ <th>gender</th>
101
+ <th>checking_status</th>
102
+ <th>duration</th>
103
+ <th>credit_history</th>
104
+ <th>purpose</th>
105
+ <th>credit_amount</th>
106
+ <th>savings_status</th>
107
+ <th>employment</th>
108
+ <th>installment_commitment</th>
109
+ <th>other_parties</th>
110
+ <th>residence_since</th>
111
+ <th>property_magnitude</th>
112
+ <th>age</th>
113
+ <th>other_payment_plans</th>
114
+ <th>housing</th>
115
+ <th>existing_credits</th>
116
+ <th>job</th>
117
+ <th>num_dependents</th>
118
+ <th>own_telephone</th>
119
+ <th>foreign_worker</th>
120
+ </tr>
121
+ </thead>
122
+ <tbody>
123
+ <tr>
124
+ <th>0</th>
125
+ <td>female</td>
126
+ <td>'no checking'</td>
127
+ <td>21</td>
128
+ <td>'no credits/all paid'</td>
129
+ <td>'new car'</td>
130
+ <td>5003</td>
131
+ <td>'no known savings'</td>
132
+ <td>'1&lt;=X&lt;4'</td>
133
+ <td>1</td>
134
+ <td>none</td>
135
+ <td>4</td>
136
+ <td>'life insurance'</td>
137
+ <td>29</td>
138
+ <td>bank</td>
139
+ <td>own</td>
140
+ <td>2</td>
141
+ <td>skilled</td>
142
+ <td>1</td>
143
+ <td>yes</td>
144
+ <td>yes</td>
145
+ </tr>
146
+ </tbody>
147
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
148
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
149
+ 0 & female & 'no checking' & 21 & 'no credits/all paid' & 'new car' & 5003 & 'no known savings' & '1<=X<4' & 1 & none & 4 & 'life insurance' & 29 & bank & own & 2 & skilled & 1 & yes & yes \\
150
+ \end{tabular}
151
+ ","{'age': 29, 'checking_status': ""'no checking'"", 'credit_amount': 5003, 'credit_history': ""'no credits/all paid'"", 'duration': 21, 'employment': ""'1<=X<4'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 1, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'bank', 'own_telephone': 'yes', 'property_magnitude': ""'life insurance'"", 'purpose': ""'new car'"", 'residence_since': 4, 'savings_status': ""'no known savings'""}",A 29-year-old female German Foreigner is applying for a loan of 5003 credits for 21 months for new car purposes. She has no checking account and no known savings. She did not take any credits at this bank or has duly paid back all credits at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 1%. She has other installment plans with a bank and 2 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 4 years. She owns life insurance property. She owns a telephone and has 1 person that she is liable to provide maintenance for.
new_data/german-fewshot-4.csv ADDED
@@ -0,0 +1,301 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Unnamed: 0,gender,checking_status,duration,credit_history,purpose,credit_amount,savings_status,employment,installment_commitment,other_parties,residence_since,property_magnitude,age,other_payment_plans,housing,existing_credits,job,num_dependents,own_telephone,foreign_worker,class,great,list,text,html,latex,json,LIFT
2
+ 0,male,'<0',60,'delayed previously',business,6836,'<100','>=7',3,none,4,'no known property',63,none,own,2,skilled,1,yes,yes,bad,"gender is male, checking_status is '<0', duration is 60, credit_history is 'delayed previously', purpose is business, credit_amount is 6836, savings_status is '<100', employment is '>=7', installment_commitment is 3, other_parties is none, residence_since is 4, property_magnitude is 'no known property', age is 63, other_payment_plans is none, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : male
3
+ - checking_status : '<0'
4
+ - duration : 60
5
+ - credit_history : 'delayed previously'
6
+ - purpose : business
7
+ - credit_amount : 6836
8
+ - savings_status : '<100'
9
+ - employment : '>=7'
10
+ - installment_commitment : 3
11
+ - other_parties : none
12
+ - residence_since : 4
13
+ - property_magnitude : 'no known property'
14
+ - age : 63
15
+ - other_payment_plans : none
16
+ - housing : own
17
+ - existing_credits : 2
18
+ - job : skilled
19
+ - num_dependents : 1
20
+ - own_telephone : yes
21
+ - foreign_worker : yes",The gender is male. The checking_status is '<0'. The duration is 60. The credit_history is 'delayed previously'. The purpose is business. The credit_amount is 6836. The savings_status is '<100'. The employment is '>=7'. The installment_commitment is 3. The other_parties is none. The residence_since is 4. The property_magnitude is 'no known property'. The age is 63. The other_payment_plans is none. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
22
+ <thead>
23
+ <tr style=""text-align: right;"">
24
+ <th></th>
25
+ <th>gender</th>
26
+ <th>checking_status</th>
27
+ <th>duration</th>
28
+ <th>credit_history</th>
29
+ <th>purpose</th>
30
+ <th>credit_amount</th>
31
+ <th>savings_status</th>
32
+ <th>employment</th>
33
+ <th>installment_commitment</th>
34
+ <th>other_parties</th>
35
+ <th>residence_since</th>
36
+ <th>property_magnitude</th>
37
+ <th>age</th>
38
+ <th>other_payment_plans</th>
39
+ <th>housing</th>
40
+ <th>existing_credits</th>
41
+ <th>job</th>
42
+ <th>num_dependents</th>
43
+ <th>own_telephone</th>
44
+ <th>foreign_worker</th>
45
+ </tr>
46
+ </thead>
47
+ <tbody>
48
+ <tr>
49
+ <th>0</th>
50
+ <td>male</td>
51
+ <td>'&lt;0'</td>
52
+ <td>60</td>
53
+ <td>'delayed previously'</td>
54
+ <td>business</td>
55
+ <td>6836</td>
56
+ <td>'&lt;100'</td>
57
+ <td>'&gt;=7'</td>
58
+ <td>3</td>
59
+ <td>none</td>
60
+ <td>4</td>
61
+ <td>'no known property'</td>
62
+ <td>63</td>
63
+ <td>none</td>
64
+ <td>own</td>
65
+ <td>2</td>
66
+ <td>skilled</td>
67
+ <td>1</td>
68
+ <td>yes</td>
69
+ <td>yes</td>
70
+ </tr>
71
+ </tbody>
72
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
73
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
74
+ 0 & male & '<0' & 60 & 'delayed previously' & business & 6836 & '<100' & '>=7' & 3 & none & 4 & 'no known property' & 63 & none & own & 2 & skilled & 1 & yes & yes \\
75
+ \end{tabular}
76
+ ","{'age': 63, 'checking_status': ""'<0'"", 'credit_amount': 6836, 'credit_history': ""'delayed previously'"", 'duration': 60, 'employment': ""'>=7'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'own', 'installment_commitment': 3, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'yes', 'property_magnitude': ""'no known property'"", 'purpose': 'business', 'residence_since': 4, 'savings_status': ""'<100'""}",A 63-year-old male German Foreigner is applying for a loan of 6836 credits for 60 months for business purposes. He has a checking account with 0 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. He has delayed paying back credits received from this bank in the past. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 3%. He has no other installment plans and 2 credits at this bank. He is employed for more than seven years. He has lived in a self-owned house for 4 years. He owns no known property. He owns a telephone and has 1 person that he is liable to provide maintenance for.
77
+ 3,female,'no checking',21,'no credits/all paid','new car',5003,'no known savings','1<=X<4',1,none,4,'life insurance',29,bank,own,2,skilled,1,yes,yes,bad,"gender is female, checking_status is 'no checking', duration is 21, credit_history is 'no credits/all paid', purpose is 'new car', credit_amount is 5003, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 1, other_parties is none, residence_since is 4, property_magnitude is 'life insurance', age is 29, other_payment_plans is bank, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : female
78
+ - checking_status : 'no checking'
79
+ - duration : 21
80
+ - credit_history : 'no credits/all paid'
81
+ - purpose : 'new car'
82
+ - credit_amount : 5003
83
+ - savings_status : 'no known savings'
84
+ - employment : '1<=X<4'
85
+ - installment_commitment : 1
86
+ - other_parties : none
87
+ - residence_since : 4
88
+ - property_magnitude : 'life insurance'
89
+ - age : 29
90
+ - other_payment_plans : bank
91
+ - housing : own
92
+ - existing_credits : 2
93
+ - job : skilled
94
+ - num_dependents : 1
95
+ - own_telephone : yes
96
+ - foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 21. The credit_history is 'no credits/all paid'. The purpose is 'new car'. The credit_amount is 5003. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 1. The other_parties is none. The residence_since is 4. The property_magnitude is 'life insurance'. The age is 29. The other_payment_plans is bank. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
97
+ <thead>
98
+ <tr style=""text-align: right;"">
99
+ <th></th>
100
+ <th>gender</th>
101
+ <th>checking_status</th>
102
+ <th>duration</th>
103
+ <th>credit_history</th>
104
+ <th>purpose</th>
105
+ <th>credit_amount</th>
106
+ <th>savings_status</th>
107
+ <th>employment</th>
108
+ <th>installment_commitment</th>
109
+ <th>other_parties</th>
110
+ <th>residence_since</th>
111
+ <th>property_magnitude</th>
112
+ <th>age</th>
113
+ <th>other_payment_plans</th>
114
+ <th>housing</th>
115
+ <th>existing_credits</th>
116
+ <th>job</th>
117
+ <th>num_dependents</th>
118
+ <th>own_telephone</th>
119
+ <th>foreign_worker</th>
120
+ </tr>
121
+ </thead>
122
+ <tbody>
123
+ <tr>
124
+ <th>0</th>
125
+ <td>female</td>
126
+ <td>'no checking'</td>
127
+ <td>21</td>
128
+ <td>'no credits/all paid'</td>
129
+ <td>'new car'</td>
130
+ <td>5003</td>
131
+ <td>'no known savings'</td>
132
+ <td>'1&lt;=X&lt;4'</td>
133
+ <td>1</td>
134
+ <td>none</td>
135
+ <td>4</td>
136
+ <td>'life insurance'</td>
137
+ <td>29</td>
138
+ <td>bank</td>
139
+ <td>own</td>
140
+ <td>2</td>
141
+ <td>skilled</td>
142
+ <td>1</td>
143
+ <td>yes</td>
144
+ <td>yes</td>
145
+ </tr>
146
+ </tbody>
147
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
148
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
149
+ 0 & female & 'no checking' & 21 & 'no credits/all paid' & 'new car' & 5003 & 'no known savings' & '1<=X<4' & 1 & none & 4 & 'life insurance' & 29 & bank & own & 2 & skilled & 1 & yes & yes \\
150
+ \end{tabular}
151
+ ","{'age': 29, 'checking_status': ""'no checking'"", 'credit_amount': 5003, 'credit_history': ""'no credits/all paid'"", 'duration': 21, 'employment': ""'1<=X<4'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 1, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'bank', 'own_telephone': 'yes', 'property_magnitude': ""'life insurance'"", 'purpose': ""'new car'"", 'residence_since': 4, 'savings_status': ""'no known savings'""}",A 29-year-old female German Foreigner is applying for a loan of 5003 credits for 21 months for new car purposes. She has no checking account and no known savings. She did not take any credits at this bank or has duly paid back all credits at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 1%. She has other installment plans with a bank and 2 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 4 years. She owns life insurance property. She owns a telephone and has 1 person that she is liable to provide maintenance for.
152
+ 1,male,'>=200',21,'critical/other existing credit',education,2319,'<100','<1',2,none,1,car,33,none,rent,1,skilled,1,none,yes,bad,"gender is male, checking_status is '>=200', duration is 21, credit_history is 'critical/other existing credit', purpose is education, credit_amount is 2319, savings_status is '<100', employment is '<1', installment_commitment is 2, other_parties is none, residence_since is 1, property_magnitude is car, age is 33, other_payment_plans is none, housing is rent, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : male
153
+ - checking_status : '>=200'
154
+ - duration : 21
155
+ - credit_history : 'critical/other existing credit'
156
+ - purpose : education
157
+ - credit_amount : 2319
158
+ - savings_status : '<100'
159
+ - employment : '<1'
160
+ - installment_commitment : 2
161
+ - other_parties : none
162
+ - residence_since : 1
163
+ - property_magnitude : car
164
+ - age : 33
165
+ - other_payment_plans : none
166
+ - housing : rent
167
+ - existing_credits : 1
168
+ - job : skilled
169
+ - num_dependents : 1
170
+ - own_telephone : none
171
+ - foreign_worker : yes",The gender is male. The checking_status is '>=200'. The duration is 21. The credit_history is 'critical/other existing credit'. The purpose is education. The credit_amount is 2319. The savings_status is '<100'. The employment is '<1'. The installment_commitment is 2. The other_parties is none. The residence_since is 1. The property_magnitude is car. The age is 33. The other_payment_plans is none. The housing is rent. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
172
+ <thead>
173
+ <tr style=""text-align: right;"">
174
+ <th></th>
175
+ <th>gender</th>
176
+ <th>checking_status</th>
177
+ <th>duration</th>
178
+ <th>credit_history</th>
179
+ <th>purpose</th>
180
+ <th>credit_amount</th>
181
+ <th>savings_status</th>
182
+ <th>employment</th>
183
+ <th>installment_commitment</th>
184
+ <th>other_parties</th>
185
+ <th>residence_since</th>
186
+ <th>property_magnitude</th>
187
+ <th>age</th>
188
+ <th>other_payment_plans</th>
189
+ <th>housing</th>
190
+ <th>existing_credits</th>
191
+ <th>job</th>
192
+ <th>num_dependents</th>
193
+ <th>own_telephone</th>
194
+ <th>foreign_worker</th>
195
+ </tr>
196
+ </thead>
197
+ <tbody>
198
+ <tr>
199
+ <th>0</th>
200
+ <td>male</td>
201
+ <td>'&gt;=200'</td>
202
+ <td>21</td>
203
+ <td>'critical/other existing credit'</td>
204
+ <td>education</td>
205
+ <td>2319</td>
206
+ <td>'&lt;100'</td>
207
+ <td>'&lt;1'</td>
208
+ <td>2</td>
209
+ <td>none</td>
210
+ <td>1</td>
211
+ <td>car</td>
212
+ <td>33</td>
213
+ <td>none</td>
214
+ <td>rent</td>
215
+ <td>1</td>
216
+ <td>skilled</td>
217
+ <td>1</td>
218
+ <td>none</td>
219
+ <td>yes</td>
220
+ </tr>
221
+ </tbody>
222
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
223
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
224
+ 0 & male & '>=200' & 21 & 'critical/other existing credit' & education & 2319 & '<100' & '<1' & 2 & none & 1 & car & 33 & none & rent & 1 & skilled & 1 & none & yes \\
225
+ \end{tabular}
226
+ ","{'age': 33, 'checking_status': ""'>=200'"", 'credit_amount': 2319, 'credit_history': ""'critical/other existing credit'"", 'duration': 21, 'employment': ""'<1'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'rent', 'installment_commitment': 2, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': 'education', 'residence_since': 1, 'savings_status': ""'<100'""}",A 33-year-old male German Foreigner is applying for a loan of 2319 credits for 21 months for education purposes. He has a checking account with 200 Deutsche Mark or more and a savings acccount with less than 100 Deutsche Mark. He has critical account or has other credits existing but not at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 2%. He has no other installment plans and 1 credits at this bank. He is employed for less than one years. He has lived in a rented apartment for 1 years. He owns a car. He does not own a telephone and has 1 person that he is liable to provide maintenance for.
227
+ 4,female,'no checking',12,'existing paid',radio/tv,886,'no known savings','1<=X<4',4,none,2,car,21,none,own,1,skilled,1,none,yes,good,"gender is female, checking_status is 'no checking', duration is 12, credit_history is 'existing paid', purpose is radio/tv, credit_amount is 886, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 4, other_parties is none, residence_since is 2, property_magnitude is car, age is 21, other_payment_plans is none, housing is own, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : female
228
+ - checking_status : 'no checking'
229
+ - duration : 12
230
+ - credit_history : 'existing paid'
231
+ - purpose : radio/tv
232
+ - credit_amount : 886
233
+ - savings_status : 'no known savings'
234
+ - employment : '1<=X<4'
235
+ - installment_commitment : 4
236
+ - other_parties : none
237
+ - residence_since : 2
238
+ - property_magnitude : car
239
+ - age : 21
240
+ - other_payment_plans : none
241
+ - housing : own
242
+ - existing_credits : 1
243
+ - job : skilled
244
+ - num_dependents : 1
245
+ - own_telephone : none
246
+ - foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 12. The credit_history is 'existing paid'. The purpose is radio/tv. The credit_amount is 886. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 4. The other_parties is none. The residence_since is 2. The property_magnitude is car. The age is 21. The other_payment_plans is none. The housing is own. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
247
+ <thead>
248
+ <tr style=""text-align: right;"">
249
+ <th></th>
250
+ <th>gender</th>
251
+ <th>checking_status</th>
252
+ <th>duration</th>
253
+ <th>credit_history</th>
254
+ <th>purpose</th>
255
+ <th>credit_amount</th>
256
+ <th>savings_status</th>
257
+ <th>employment</th>
258
+ <th>installment_commitment</th>
259
+ <th>other_parties</th>
260
+ <th>residence_since</th>
261
+ <th>property_magnitude</th>
262
+ <th>age</th>
263
+ <th>other_payment_plans</th>
264
+ <th>housing</th>
265
+ <th>existing_credits</th>
266
+ <th>job</th>
267
+ <th>num_dependents</th>
268
+ <th>own_telephone</th>
269
+ <th>foreign_worker</th>
270
+ </tr>
271
+ </thead>
272
+ <tbody>
273
+ <tr>
274
+ <th>0</th>
275
+ <td>female</td>
276
+ <td>'no checking'</td>
277
+ <td>12</td>
278
+ <td>'existing paid'</td>
279
+ <td>radio/tv</td>
280
+ <td>886</td>
281
+ <td>'no known savings'</td>
282
+ <td>'1&lt;=X&lt;4'</td>
283
+ <td>4</td>
284
+ <td>none</td>
285
+ <td>2</td>
286
+ <td>car</td>
287
+ <td>21</td>
288
+ <td>none</td>
289
+ <td>own</td>
290
+ <td>1</td>
291
+ <td>skilled</td>
292
+ <td>1</td>
293
+ <td>none</td>
294
+ <td>yes</td>
295
+ </tr>
296
+ </tbody>
297
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
298
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
299
+ 0 & female & 'no checking' & 12 & 'existing paid' & radio/tv & 886 & 'no known savings' & '1<=X<4' & 4 & none & 2 & car & 21 & none & own & 1 & skilled & 1 & none & yes \\
300
+ \end{tabular}
301
+ ","{'age': 21, 'checking_status': ""'no checking'"", 'credit_amount': 886, 'credit_history': ""'existing paid'"", 'duration': 12, 'employment': ""'1<=X<4'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 4, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': 'radio/tv', 'residence_since': 2, 'savings_status': ""'no known savings'""}",A 21-year-old female German Foreigner is applying for a loan of 886 credits for 12 months for radio or tv purposes. She has no checking account and no known savings. She has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 1 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 2 years. She owns a car. She does not own a telephone and has 1 person that she is liable to provide maintenance for.
new_data/german-fewshot-6.csv ADDED
@@ -0,0 +1,451 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Unnamed: 0,gender,checking_status,duration,credit_history,purpose,credit_amount,savings_status,employment,installment_commitment,other_parties,residence_since,property_magnitude,age,other_payment_plans,housing,existing_credits,job,num_dependents,own_telephone,foreign_worker,class,great,list,text,html,latex,json,LIFT
2
+ 0,male,'<0',60,'delayed previously',business,6836,'<100','>=7',3,none,4,'no known property',63,none,own,2,skilled,1,yes,yes,bad,"gender is male, checking_status is '<0', duration is 60, credit_history is 'delayed previously', purpose is business, credit_amount is 6836, savings_status is '<100', employment is '>=7', installment_commitment is 3, other_parties is none, residence_since is 4, property_magnitude is 'no known property', age is 63, other_payment_plans is none, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : male
3
+ - checking_status : '<0'
4
+ - duration : 60
5
+ - credit_history : 'delayed previously'
6
+ - purpose : business
7
+ - credit_amount : 6836
8
+ - savings_status : '<100'
9
+ - employment : '>=7'
10
+ - installment_commitment : 3
11
+ - other_parties : none
12
+ - residence_since : 4
13
+ - property_magnitude : 'no known property'
14
+ - age : 63
15
+ - other_payment_plans : none
16
+ - housing : own
17
+ - existing_credits : 2
18
+ - job : skilled
19
+ - num_dependents : 1
20
+ - own_telephone : yes
21
+ - foreign_worker : yes",The gender is male. The checking_status is '<0'. The duration is 60. The credit_history is 'delayed previously'. The purpose is business. The credit_amount is 6836. The savings_status is '<100'. The employment is '>=7'. The installment_commitment is 3. The other_parties is none. The residence_since is 4. The property_magnitude is 'no known property'. The age is 63. The other_payment_plans is none. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
22
+ <thead>
23
+ <tr style=""text-align: right;"">
24
+ <th></th>
25
+ <th>gender</th>
26
+ <th>checking_status</th>
27
+ <th>duration</th>
28
+ <th>credit_history</th>
29
+ <th>purpose</th>
30
+ <th>credit_amount</th>
31
+ <th>savings_status</th>
32
+ <th>employment</th>
33
+ <th>installment_commitment</th>
34
+ <th>other_parties</th>
35
+ <th>residence_since</th>
36
+ <th>property_magnitude</th>
37
+ <th>age</th>
38
+ <th>other_payment_plans</th>
39
+ <th>housing</th>
40
+ <th>existing_credits</th>
41
+ <th>job</th>
42
+ <th>num_dependents</th>
43
+ <th>own_telephone</th>
44
+ <th>foreign_worker</th>
45
+ </tr>
46
+ </thead>
47
+ <tbody>
48
+ <tr>
49
+ <th>0</th>
50
+ <td>male</td>
51
+ <td>'&lt;0'</td>
52
+ <td>60</td>
53
+ <td>'delayed previously'</td>
54
+ <td>business</td>
55
+ <td>6836</td>
56
+ <td>'&lt;100'</td>
57
+ <td>'&gt;=7'</td>
58
+ <td>3</td>
59
+ <td>none</td>
60
+ <td>4</td>
61
+ <td>'no known property'</td>
62
+ <td>63</td>
63
+ <td>none</td>
64
+ <td>own</td>
65
+ <td>2</td>
66
+ <td>skilled</td>
67
+ <td>1</td>
68
+ <td>yes</td>
69
+ <td>yes</td>
70
+ </tr>
71
+ </tbody>
72
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
73
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
74
+ 0 & male & '<0' & 60 & 'delayed previously' & business & 6836 & '<100' & '>=7' & 3 & none & 4 & 'no known property' & 63 & none & own & 2 & skilled & 1 & yes & yes \\
75
+ \end{tabular}
76
+ ","{'age': 63, 'checking_status': ""'<0'"", 'credit_amount': 6836, 'credit_history': ""'delayed previously'"", 'duration': 60, 'employment': ""'>=7'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'own', 'installment_commitment': 3, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'yes', 'property_magnitude': ""'no known property'"", 'purpose': 'business', 'residence_since': 4, 'savings_status': ""'<100'""}",A 63-year-old male German Foreigner is applying for a loan of 6836 credits for 60 months for business purposes. He has a checking account with 0 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. He has delayed paying back credits received from this bank in the past. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 3%. He has no other installment plans and 2 credits at this bank. He is employed for more than seven years. He has lived in a self-owned house for 4 years. He owns no known property. He owns a telephone and has 1 person that he is liable to provide maintenance for.
77
+ 3,female,'no checking',21,'no credits/all paid','new car',5003,'no known savings','1<=X<4',1,none,4,'life insurance',29,bank,own,2,skilled,1,yes,yes,bad,"gender is female, checking_status is 'no checking', duration is 21, credit_history is 'no credits/all paid', purpose is 'new car', credit_amount is 5003, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 1, other_parties is none, residence_since is 4, property_magnitude is 'life insurance', age is 29, other_payment_plans is bank, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : female
78
+ - checking_status : 'no checking'
79
+ - duration : 21
80
+ - credit_history : 'no credits/all paid'
81
+ - purpose : 'new car'
82
+ - credit_amount : 5003
83
+ - savings_status : 'no known savings'
84
+ - employment : '1<=X<4'
85
+ - installment_commitment : 1
86
+ - other_parties : none
87
+ - residence_since : 4
88
+ - property_magnitude : 'life insurance'
89
+ - age : 29
90
+ - other_payment_plans : bank
91
+ - housing : own
92
+ - existing_credits : 2
93
+ - job : skilled
94
+ - num_dependents : 1
95
+ - own_telephone : yes
96
+ - foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 21. The credit_history is 'no credits/all paid'. The purpose is 'new car'. The credit_amount is 5003. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 1. The other_parties is none. The residence_since is 4. The property_magnitude is 'life insurance'. The age is 29. The other_payment_plans is bank. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
97
+ <thead>
98
+ <tr style=""text-align: right;"">
99
+ <th></th>
100
+ <th>gender</th>
101
+ <th>checking_status</th>
102
+ <th>duration</th>
103
+ <th>credit_history</th>
104
+ <th>purpose</th>
105
+ <th>credit_amount</th>
106
+ <th>savings_status</th>
107
+ <th>employment</th>
108
+ <th>installment_commitment</th>
109
+ <th>other_parties</th>
110
+ <th>residence_since</th>
111
+ <th>property_magnitude</th>
112
+ <th>age</th>
113
+ <th>other_payment_plans</th>
114
+ <th>housing</th>
115
+ <th>existing_credits</th>
116
+ <th>job</th>
117
+ <th>num_dependents</th>
118
+ <th>own_telephone</th>
119
+ <th>foreign_worker</th>
120
+ </tr>
121
+ </thead>
122
+ <tbody>
123
+ <tr>
124
+ <th>0</th>
125
+ <td>female</td>
126
+ <td>'no checking'</td>
127
+ <td>21</td>
128
+ <td>'no credits/all paid'</td>
129
+ <td>'new car'</td>
130
+ <td>5003</td>
131
+ <td>'no known savings'</td>
132
+ <td>'1&lt;=X&lt;4'</td>
133
+ <td>1</td>
134
+ <td>none</td>
135
+ <td>4</td>
136
+ <td>'life insurance'</td>
137
+ <td>29</td>
138
+ <td>bank</td>
139
+ <td>own</td>
140
+ <td>2</td>
141
+ <td>skilled</td>
142
+ <td>1</td>
143
+ <td>yes</td>
144
+ <td>yes</td>
145
+ </tr>
146
+ </tbody>
147
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
148
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
149
+ 0 & female & 'no checking' & 21 & 'no credits/all paid' & 'new car' & 5003 & 'no known savings' & '1<=X<4' & 1 & none & 4 & 'life insurance' & 29 & bank & own & 2 & skilled & 1 & yes & yes \\
150
+ \end{tabular}
151
+ ","{'age': 29, 'checking_status': ""'no checking'"", 'credit_amount': 5003, 'credit_history': ""'no credits/all paid'"", 'duration': 21, 'employment': ""'1<=X<4'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 1, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'bank', 'own_telephone': 'yes', 'property_magnitude': ""'life insurance'"", 'purpose': ""'new car'"", 'residence_since': 4, 'savings_status': ""'no known savings'""}",A 29-year-old female German Foreigner is applying for a loan of 5003 credits for 21 months for new car purposes. She has no checking account and no known savings. She did not take any credits at this bank or has duly paid back all credits at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 1%. She has other installment plans with a bank and 2 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 4 years. She owns life insurance property. She owns a telephone and has 1 person that she is liable to provide maintenance for.
152
+ 1,male,'>=200',21,'critical/other existing credit',education,2319,'<100','<1',2,none,1,car,33,none,rent,1,skilled,1,none,yes,bad,"gender is male, checking_status is '>=200', duration is 21, credit_history is 'critical/other existing credit', purpose is education, credit_amount is 2319, savings_status is '<100', employment is '<1', installment_commitment is 2, other_parties is none, residence_since is 1, property_magnitude is car, age is 33, other_payment_plans is none, housing is rent, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : male
153
+ - checking_status : '>=200'
154
+ - duration : 21
155
+ - credit_history : 'critical/other existing credit'
156
+ - purpose : education
157
+ - credit_amount : 2319
158
+ - savings_status : '<100'
159
+ - employment : '<1'
160
+ - installment_commitment : 2
161
+ - other_parties : none
162
+ - residence_since : 1
163
+ - property_magnitude : car
164
+ - age : 33
165
+ - other_payment_plans : none
166
+ - housing : rent
167
+ - existing_credits : 1
168
+ - job : skilled
169
+ - num_dependents : 1
170
+ - own_telephone : none
171
+ - foreign_worker : yes",The gender is male. The checking_status is '>=200'. The duration is 21. The credit_history is 'critical/other existing credit'. The purpose is education. The credit_amount is 2319. The savings_status is '<100'. The employment is '<1'. The installment_commitment is 2. The other_parties is none. The residence_since is 1. The property_magnitude is car. The age is 33. The other_payment_plans is none. The housing is rent. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
172
+ <thead>
173
+ <tr style=""text-align: right;"">
174
+ <th></th>
175
+ <th>gender</th>
176
+ <th>checking_status</th>
177
+ <th>duration</th>
178
+ <th>credit_history</th>
179
+ <th>purpose</th>
180
+ <th>credit_amount</th>
181
+ <th>savings_status</th>
182
+ <th>employment</th>
183
+ <th>installment_commitment</th>
184
+ <th>other_parties</th>
185
+ <th>residence_since</th>
186
+ <th>property_magnitude</th>
187
+ <th>age</th>
188
+ <th>other_payment_plans</th>
189
+ <th>housing</th>
190
+ <th>existing_credits</th>
191
+ <th>job</th>
192
+ <th>num_dependents</th>
193
+ <th>own_telephone</th>
194
+ <th>foreign_worker</th>
195
+ </tr>
196
+ </thead>
197
+ <tbody>
198
+ <tr>
199
+ <th>0</th>
200
+ <td>male</td>
201
+ <td>'&gt;=200'</td>
202
+ <td>21</td>
203
+ <td>'critical/other existing credit'</td>
204
+ <td>education</td>
205
+ <td>2319</td>
206
+ <td>'&lt;100'</td>
207
+ <td>'&lt;1'</td>
208
+ <td>2</td>
209
+ <td>none</td>
210
+ <td>1</td>
211
+ <td>car</td>
212
+ <td>33</td>
213
+ <td>none</td>
214
+ <td>rent</td>
215
+ <td>1</td>
216
+ <td>skilled</td>
217
+ <td>1</td>
218
+ <td>none</td>
219
+ <td>yes</td>
220
+ </tr>
221
+ </tbody>
222
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
223
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
224
+ 0 & male & '>=200' & 21 & 'critical/other existing credit' & education & 2319 & '<100' & '<1' & 2 & none & 1 & car & 33 & none & rent & 1 & skilled & 1 & none & yes \\
225
+ \end{tabular}
226
+ ","{'age': 33, 'checking_status': ""'>=200'"", 'credit_amount': 2319, 'credit_history': ""'critical/other existing credit'"", 'duration': 21, 'employment': ""'<1'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'rent', 'installment_commitment': 2, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': 'education', 'residence_since': 1, 'savings_status': ""'<100'""}",A 33-year-old male German Foreigner is applying for a loan of 2319 credits for 21 months for education purposes. He has a checking account with 200 Deutsche Mark or more and a savings acccount with less than 100 Deutsche Mark. He has critical account or has other credits existing but not at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 2%. He has no other installment plans and 1 credits at this bank. He is employed for less than one years. He has lived in a rented apartment for 1 years. He owns a car. He does not own a telephone and has 1 person that he is liable to provide maintenance for.
227
+ 4,female,'no checking',12,'existing paid',radio/tv,886,'no known savings','1<=X<4',4,none,2,car,21,none,own,1,skilled,1,none,yes,good,"gender is female, checking_status is 'no checking', duration is 12, credit_history is 'existing paid', purpose is radio/tv, credit_amount is 886, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 4, other_parties is none, residence_since is 2, property_magnitude is car, age is 21, other_payment_plans is none, housing is own, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : female
228
+ - checking_status : 'no checking'
229
+ - duration : 12
230
+ - credit_history : 'existing paid'
231
+ - purpose : radio/tv
232
+ - credit_amount : 886
233
+ - savings_status : 'no known savings'
234
+ - employment : '1<=X<4'
235
+ - installment_commitment : 4
236
+ - other_parties : none
237
+ - residence_since : 2
238
+ - property_magnitude : car
239
+ - age : 21
240
+ - other_payment_plans : none
241
+ - housing : own
242
+ - existing_credits : 1
243
+ - job : skilled
244
+ - num_dependents : 1
245
+ - own_telephone : none
246
+ - foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 12. The credit_history is 'existing paid'. The purpose is radio/tv. The credit_amount is 886. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 4. The other_parties is none. The residence_since is 2. The property_magnitude is car. The age is 21. The other_payment_plans is none. The housing is own. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
247
+ <thead>
248
+ <tr style=""text-align: right;"">
249
+ <th></th>
250
+ <th>gender</th>
251
+ <th>checking_status</th>
252
+ <th>duration</th>
253
+ <th>credit_history</th>
254
+ <th>purpose</th>
255
+ <th>credit_amount</th>
256
+ <th>savings_status</th>
257
+ <th>employment</th>
258
+ <th>installment_commitment</th>
259
+ <th>other_parties</th>
260
+ <th>residence_since</th>
261
+ <th>property_magnitude</th>
262
+ <th>age</th>
263
+ <th>other_payment_plans</th>
264
+ <th>housing</th>
265
+ <th>existing_credits</th>
266
+ <th>job</th>
267
+ <th>num_dependents</th>
268
+ <th>own_telephone</th>
269
+ <th>foreign_worker</th>
270
+ </tr>
271
+ </thead>
272
+ <tbody>
273
+ <tr>
274
+ <th>0</th>
275
+ <td>female</td>
276
+ <td>'no checking'</td>
277
+ <td>12</td>
278
+ <td>'existing paid'</td>
279
+ <td>radio/tv</td>
280
+ <td>886</td>
281
+ <td>'no known savings'</td>
282
+ <td>'1&lt;=X&lt;4'</td>
283
+ <td>4</td>
284
+ <td>none</td>
285
+ <td>2</td>
286
+ <td>car</td>
287
+ <td>21</td>
288
+ <td>none</td>
289
+ <td>own</td>
290
+ <td>1</td>
291
+ <td>skilled</td>
292
+ <td>1</td>
293
+ <td>none</td>
294
+ <td>yes</td>
295
+ </tr>
296
+ </tbody>
297
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
298
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
299
+ 0 & female & 'no checking' & 12 & 'existing paid' & radio/tv & 886 & 'no known savings' & '1<=X<4' & 4 & none & 2 & car & 21 & none & own & 1 & skilled & 1 & none & yes \\
300
+ \end{tabular}
301
+ ","{'age': 21, 'checking_status': ""'no checking'"", 'credit_amount': 886, 'credit_history': ""'existing paid'"", 'duration': 12, 'employment': ""'1<=X<4'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 4, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': 'radio/tv', 'residence_since': 2, 'savings_status': ""'no known savings'""}",A 21-year-old female German Foreigner is applying for a loan of 886 credits for 12 months for radio or tv purposes. She has no checking account and no known savings. She has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 1 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 2 years. She owns a car. She does not own a telephone and has 1 person that she is liable to provide maintenance for.
302
+ 2,male,'no checking',6,'existing paid','used car',1236,'500<=X<1000','1<=X<4',2,none,4,'life insurance',50,none,rent,1,skilled,1,none,yes,good,"gender is male, checking_status is 'no checking', duration is 6, credit_history is 'existing paid', purpose is 'used car', credit_amount is 1236, savings_status is '500<=X<1000', employment is '1<=X<4', installment_commitment is 2, other_parties is none, residence_since is 4, property_magnitude is 'life insurance', age is 50, other_payment_plans is none, housing is rent, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : male
303
+ - checking_status : 'no checking'
304
+ - duration : 6
305
+ - credit_history : 'existing paid'
306
+ - purpose : 'used car'
307
+ - credit_amount : 1236
308
+ - savings_status : '500<=X<1000'
309
+ - employment : '1<=X<4'
310
+ - installment_commitment : 2
311
+ - other_parties : none
312
+ - residence_since : 4
313
+ - property_magnitude : 'life insurance'
314
+ - age : 50
315
+ - other_payment_plans : none
316
+ - housing : rent
317
+ - existing_credits : 1
318
+ - job : skilled
319
+ - num_dependents : 1
320
+ - own_telephone : none
321
+ - foreign_worker : yes",The gender is male. The checking_status is 'no checking'. The duration is 6. The credit_history is 'existing paid'. The purpose is 'used car'. The credit_amount is 1236. The savings_status is '500<=X<1000'. The employment is '1<=X<4'. The installment_commitment is 2. The other_parties is none. The residence_since is 4. The property_magnitude is 'life insurance'. The age is 50. The other_payment_plans is none. The housing is rent. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
322
+ <thead>
323
+ <tr style=""text-align: right;"">
324
+ <th></th>
325
+ <th>gender</th>
326
+ <th>checking_status</th>
327
+ <th>duration</th>
328
+ <th>credit_history</th>
329
+ <th>purpose</th>
330
+ <th>credit_amount</th>
331
+ <th>savings_status</th>
332
+ <th>employment</th>
333
+ <th>installment_commitment</th>
334
+ <th>other_parties</th>
335
+ <th>residence_since</th>
336
+ <th>property_magnitude</th>
337
+ <th>age</th>
338
+ <th>other_payment_plans</th>
339
+ <th>housing</th>
340
+ <th>existing_credits</th>
341
+ <th>job</th>
342
+ <th>num_dependents</th>
343
+ <th>own_telephone</th>
344
+ <th>foreign_worker</th>
345
+ </tr>
346
+ </thead>
347
+ <tbody>
348
+ <tr>
349
+ <th>0</th>
350
+ <td>male</td>
351
+ <td>'no checking'</td>
352
+ <td>6</td>
353
+ <td>'existing paid'</td>
354
+ <td>'used car'</td>
355
+ <td>1236</td>
356
+ <td>'500&lt;=X&lt;1000'</td>
357
+ <td>'1&lt;=X&lt;4'</td>
358
+ <td>2</td>
359
+ <td>none</td>
360
+ <td>4</td>
361
+ <td>'life insurance'</td>
362
+ <td>50</td>
363
+ <td>none</td>
364
+ <td>rent</td>
365
+ <td>1</td>
366
+ <td>skilled</td>
367
+ <td>1</td>
368
+ <td>none</td>
369
+ <td>yes</td>
370
+ </tr>
371
+ </tbody>
372
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
373
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
374
+ 0 & male & 'no checking' & 6 & 'existing paid' & 'used car' & 1236 & '500<=X<1000' & '1<=X<4' & 2 & none & 4 & 'life insurance' & 50 & none & rent & 1 & skilled & 1 & none & yes \\
375
+ \end{tabular}
376
+ ","{'age': 50, 'checking_status': ""'no checking'"", 'credit_amount': 1236, 'credit_history': ""'existing paid'"", 'duration': 6, 'employment': ""'1<=X<4'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'rent', 'installment_commitment': 2, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': ""'life insurance'"", 'purpose': ""'used car'"", 'residence_since': 4, 'savings_status': ""'500<=X<1000'""}",A 50-year-old male German Foreigner is applying for a loan of 1236 credits for 6 months for used car purposes. He has no checking account and a savings with more than 500 Deutsche Mark but less than 1000 Deutsche Mark. He has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 2%. He has no other installment plans and 1 credits at this bank. He is employed for more than one year but less than four years. He has lived in a rented apartment for 4 years. He owns life insurance property. He does not own a telephone and has 1 person that he is liable to provide maintenance for.
377
+ 5,female,'<0',24,'existing paid','new car',1442,'<100','4<=X<7',4,none,4,car,23,none,rent,2,skilled,1,none,yes,bad,"gender is female, checking_status is '<0', duration is 24, credit_history is 'existing paid', purpose is 'new car', credit_amount is 1442, savings_status is '<100', employment is '4<=X<7', installment_commitment is 4, other_parties is none, residence_since is 4, property_magnitude is car, age is 23, other_payment_plans is none, housing is rent, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : female
378
+ - checking_status : '<0'
379
+ - duration : 24
380
+ - credit_history : 'existing paid'
381
+ - purpose : 'new car'
382
+ - credit_amount : 1442
383
+ - savings_status : '<100'
384
+ - employment : '4<=X<7'
385
+ - installment_commitment : 4
386
+ - other_parties : none
387
+ - residence_since : 4
388
+ - property_magnitude : car
389
+ - age : 23
390
+ - other_payment_plans : none
391
+ - housing : rent
392
+ - existing_credits : 2
393
+ - job : skilled
394
+ - num_dependents : 1
395
+ - own_telephone : none
396
+ - foreign_worker : yes",The gender is female. The checking_status is '<0'. The duration is 24. The credit_history is 'existing paid'. The purpose is 'new car'. The credit_amount is 1442. The savings_status is '<100'. The employment is '4<=X<7'. The installment_commitment is 4. The other_parties is none. The residence_since is 4. The property_magnitude is car. The age is 23. The other_payment_plans is none. The housing is rent. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
397
+ <thead>
398
+ <tr style=""text-align: right;"">
399
+ <th></th>
400
+ <th>gender</th>
401
+ <th>checking_status</th>
402
+ <th>duration</th>
403
+ <th>credit_history</th>
404
+ <th>purpose</th>
405
+ <th>credit_amount</th>
406
+ <th>savings_status</th>
407
+ <th>employment</th>
408
+ <th>installment_commitment</th>
409
+ <th>other_parties</th>
410
+ <th>residence_since</th>
411
+ <th>property_magnitude</th>
412
+ <th>age</th>
413
+ <th>other_payment_plans</th>
414
+ <th>housing</th>
415
+ <th>existing_credits</th>
416
+ <th>job</th>
417
+ <th>num_dependents</th>
418
+ <th>own_telephone</th>
419
+ <th>foreign_worker</th>
420
+ </tr>
421
+ </thead>
422
+ <tbody>
423
+ <tr>
424
+ <th>0</th>
425
+ <td>female</td>
426
+ <td>'&lt;0'</td>
427
+ <td>24</td>
428
+ <td>'existing paid'</td>
429
+ <td>'new car'</td>
430
+ <td>1442</td>
431
+ <td>'&lt;100'</td>
432
+ <td>'4&lt;=X&lt;7'</td>
433
+ <td>4</td>
434
+ <td>none</td>
435
+ <td>4</td>
436
+ <td>car</td>
437
+ <td>23</td>
438
+ <td>none</td>
439
+ <td>rent</td>
440
+ <td>2</td>
441
+ <td>skilled</td>
442
+ <td>1</td>
443
+ <td>none</td>
444
+ <td>yes</td>
445
+ </tr>
446
+ </tbody>
447
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
448
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
449
+ 0 & female & '<0' & 24 & 'existing paid' & 'new car' & 1442 & '<100' & '4<=X<7' & 4 & none & 4 & car & 23 & none & rent & 2 & skilled & 1 & none & yes \\
450
+ \end{tabular}
451
+ ","{'age': 23, 'checking_status': ""'<0'"", 'credit_amount': 1442, 'credit_history': ""'existing paid'"", 'duration': 24, 'employment': ""'4<=X<7'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'rent', 'installment_commitment': 4, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': ""'new car'"", 'residence_since': 4, 'savings_status': ""'<100'""}",A 23-year-old female German Foreigner is applying for a loan of 1442 credits for 24 months for new car purposes. She has a checking account with 0 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. She has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 2 credits at this bank. She is employed for more than four years but less than seven years. She has lived in a rented apartment for 4 years. She owns a car. She does not own a telephone and has 1 person that she is liable to provide maintenance for.
new_data/german-fewshot-8.csv ADDED
@@ -0,0 +1,601 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Unnamed: 0,gender,checking_status,duration,credit_history,purpose,credit_amount,savings_status,employment,installment_commitment,other_parties,residence_since,property_magnitude,age,other_payment_plans,housing,existing_credits,job,num_dependents,own_telephone,foreign_worker,class,great,list,text,html,latex,json,LIFT
2
+ 0,male,'<0',60,'delayed previously',business,6836,'<100','>=7',3,none,4,'no known property',63,none,own,2,skilled,1,yes,yes,bad,"gender is male, checking_status is '<0', duration is 60, credit_history is 'delayed previously', purpose is business, credit_amount is 6836, savings_status is '<100', employment is '>=7', installment_commitment is 3, other_parties is none, residence_since is 4, property_magnitude is 'no known property', age is 63, other_payment_plans is none, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : male
3
+ - checking_status : '<0'
4
+ - duration : 60
5
+ - credit_history : 'delayed previously'
6
+ - purpose : business
7
+ - credit_amount : 6836
8
+ - savings_status : '<100'
9
+ - employment : '>=7'
10
+ - installment_commitment : 3
11
+ - other_parties : none
12
+ - residence_since : 4
13
+ - property_magnitude : 'no known property'
14
+ - age : 63
15
+ - other_payment_plans : none
16
+ - housing : own
17
+ - existing_credits : 2
18
+ - job : skilled
19
+ - num_dependents : 1
20
+ - own_telephone : yes
21
+ - foreign_worker : yes",The gender is male. The checking_status is '<0'. The duration is 60. The credit_history is 'delayed previously'. The purpose is business. The credit_amount is 6836. The savings_status is '<100'. The employment is '>=7'. The installment_commitment is 3. The other_parties is none. The residence_since is 4. The property_magnitude is 'no known property'. The age is 63. The other_payment_plans is none. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
22
+ <thead>
23
+ <tr style=""text-align: right;"">
24
+ <th></th>
25
+ <th>gender</th>
26
+ <th>checking_status</th>
27
+ <th>duration</th>
28
+ <th>credit_history</th>
29
+ <th>purpose</th>
30
+ <th>credit_amount</th>
31
+ <th>savings_status</th>
32
+ <th>employment</th>
33
+ <th>installment_commitment</th>
34
+ <th>other_parties</th>
35
+ <th>residence_since</th>
36
+ <th>property_magnitude</th>
37
+ <th>age</th>
38
+ <th>other_payment_plans</th>
39
+ <th>housing</th>
40
+ <th>existing_credits</th>
41
+ <th>job</th>
42
+ <th>num_dependents</th>
43
+ <th>own_telephone</th>
44
+ <th>foreign_worker</th>
45
+ </tr>
46
+ </thead>
47
+ <tbody>
48
+ <tr>
49
+ <th>0</th>
50
+ <td>male</td>
51
+ <td>'&lt;0'</td>
52
+ <td>60</td>
53
+ <td>'delayed previously'</td>
54
+ <td>business</td>
55
+ <td>6836</td>
56
+ <td>'&lt;100'</td>
57
+ <td>'&gt;=7'</td>
58
+ <td>3</td>
59
+ <td>none</td>
60
+ <td>4</td>
61
+ <td>'no known property'</td>
62
+ <td>63</td>
63
+ <td>none</td>
64
+ <td>own</td>
65
+ <td>2</td>
66
+ <td>skilled</td>
67
+ <td>1</td>
68
+ <td>yes</td>
69
+ <td>yes</td>
70
+ </tr>
71
+ </tbody>
72
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
73
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
74
+ 0 & male & '<0' & 60 & 'delayed previously' & business & 6836 & '<100' & '>=7' & 3 & none & 4 & 'no known property' & 63 & none & own & 2 & skilled & 1 & yes & yes \\
75
+ \end{tabular}
76
+ ","{'age': 63, 'checking_status': ""'<0'"", 'credit_amount': 6836, 'credit_history': ""'delayed previously'"", 'duration': 60, 'employment': ""'>=7'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'own', 'installment_commitment': 3, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'yes', 'property_magnitude': ""'no known property'"", 'purpose': 'business', 'residence_since': 4, 'savings_status': ""'<100'""}",A 63-year-old male German Foreigner is applying for a loan of 6836 credits for 60 months for business purposes. He has a checking account with 0 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. He has delayed paying back credits received from this bank in the past. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 3%. He has no other installment plans and 2 credits at this bank. He is employed for more than seven years. He has lived in a self-owned house for 4 years. He owns no known property. He owns a telephone and has 1 person that he is liable to provide maintenance for.
77
+ 3,female,'no checking',21,'no credits/all paid','new car',5003,'no known savings','1<=X<4',1,none,4,'life insurance',29,bank,own,2,skilled,1,yes,yes,bad,"gender is female, checking_status is 'no checking', duration is 21, credit_history is 'no credits/all paid', purpose is 'new car', credit_amount is 5003, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 1, other_parties is none, residence_since is 4, property_magnitude is 'life insurance', age is 29, other_payment_plans is bank, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : female
78
+ - checking_status : 'no checking'
79
+ - duration : 21
80
+ - credit_history : 'no credits/all paid'
81
+ - purpose : 'new car'
82
+ - credit_amount : 5003
83
+ - savings_status : 'no known savings'
84
+ - employment : '1<=X<4'
85
+ - installment_commitment : 1
86
+ - other_parties : none
87
+ - residence_since : 4
88
+ - property_magnitude : 'life insurance'
89
+ - age : 29
90
+ - other_payment_plans : bank
91
+ - housing : own
92
+ - existing_credits : 2
93
+ - job : skilled
94
+ - num_dependents : 1
95
+ - own_telephone : yes
96
+ - foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 21. The credit_history is 'no credits/all paid'. The purpose is 'new car'. The credit_amount is 5003. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 1. The other_parties is none. The residence_since is 4. The property_magnitude is 'life insurance'. The age is 29. The other_payment_plans is bank. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
97
+ <thead>
98
+ <tr style=""text-align: right;"">
99
+ <th></th>
100
+ <th>gender</th>
101
+ <th>checking_status</th>
102
+ <th>duration</th>
103
+ <th>credit_history</th>
104
+ <th>purpose</th>
105
+ <th>credit_amount</th>
106
+ <th>savings_status</th>
107
+ <th>employment</th>
108
+ <th>installment_commitment</th>
109
+ <th>other_parties</th>
110
+ <th>residence_since</th>
111
+ <th>property_magnitude</th>
112
+ <th>age</th>
113
+ <th>other_payment_plans</th>
114
+ <th>housing</th>
115
+ <th>existing_credits</th>
116
+ <th>job</th>
117
+ <th>num_dependents</th>
118
+ <th>own_telephone</th>
119
+ <th>foreign_worker</th>
120
+ </tr>
121
+ </thead>
122
+ <tbody>
123
+ <tr>
124
+ <th>0</th>
125
+ <td>female</td>
126
+ <td>'no checking'</td>
127
+ <td>21</td>
128
+ <td>'no credits/all paid'</td>
129
+ <td>'new car'</td>
130
+ <td>5003</td>
131
+ <td>'no known savings'</td>
132
+ <td>'1&lt;=X&lt;4'</td>
133
+ <td>1</td>
134
+ <td>none</td>
135
+ <td>4</td>
136
+ <td>'life insurance'</td>
137
+ <td>29</td>
138
+ <td>bank</td>
139
+ <td>own</td>
140
+ <td>2</td>
141
+ <td>skilled</td>
142
+ <td>1</td>
143
+ <td>yes</td>
144
+ <td>yes</td>
145
+ </tr>
146
+ </tbody>
147
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
148
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
149
+ 0 & female & 'no checking' & 21 & 'no credits/all paid' & 'new car' & 5003 & 'no known savings' & '1<=X<4' & 1 & none & 4 & 'life insurance' & 29 & bank & own & 2 & skilled & 1 & yes & yes \\
150
+ \end{tabular}
151
+ ","{'age': 29, 'checking_status': ""'no checking'"", 'credit_amount': 5003, 'credit_history': ""'no credits/all paid'"", 'duration': 21, 'employment': ""'1<=X<4'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 1, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'bank', 'own_telephone': 'yes', 'property_magnitude': ""'life insurance'"", 'purpose': ""'new car'"", 'residence_since': 4, 'savings_status': ""'no known savings'""}",A 29-year-old female German Foreigner is applying for a loan of 5003 credits for 21 months for new car purposes. She has no checking account and no known savings. She did not take any credits at this bank or has duly paid back all credits at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 1%. She has other installment plans with a bank and 2 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 4 years. She owns life insurance property. She owns a telephone and has 1 person that she is liable to provide maintenance for.
152
+ 1,male,'>=200',21,'critical/other existing credit',education,2319,'<100','<1',2,none,1,car,33,none,rent,1,skilled,1,none,yes,bad,"gender is male, checking_status is '>=200', duration is 21, credit_history is 'critical/other existing credit', purpose is education, credit_amount is 2319, savings_status is '<100', employment is '<1', installment_commitment is 2, other_parties is none, residence_since is 1, property_magnitude is car, age is 33, other_payment_plans is none, housing is rent, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : male
153
+ - checking_status : '>=200'
154
+ - duration : 21
155
+ - credit_history : 'critical/other existing credit'
156
+ - purpose : education
157
+ - credit_amount : 2319
158
+ - savings_status : '<100'
159
+ - employment : '<1'
160
+ - installment_commitment : 2
161
+ - other_parties : none
162
+ - residence_since : 1
163
+ - property_magnitude : car
164
+ - age : 33
165
+ - other_payment_plans : none
166
+ - housing : rent
167
+ - existing_credits : 1
168
+ - job : skilled
169
+ - num_dependents : 1
170
+ - own_telephone : none
171
+ - foreign_worker : yes",The gender is male. The checking_status is '>=200'. The duration is 21. The credit_history is 'critical/other existing credit'. The purpose is education. The credit_amount is 2319. The savings_status is '<100'. The employment is '<1'. The installment_commitment is 2. The other_parties is none. The residence_since is 1. The property_magnitude is car. The age is 33. The other_payment_plans is none. The housing is rent. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
172
+ <thead>
173
+ <tr style=""text-align: right;"">
174
+ <th></th>
175
+ <th>gender</th>
176
+ <th>checking_status</th>
177
+ <th>duration</th>
178
+ <th>credit_history</th>
179
+ <th>purpose</th>
180
+ <th>credit_amount</th>
181
+ <th>savings_status</th>
182
+ <th>employment</th>
183
+ <th>installment_commitment</th>
184
+ <th>other_parties</th>
185
+ <th>residence_since</th>
186
+ <th>property_magnitude</th>
187
+ <th>age</th>
188
+ <th>other_payment_plans</th>
189
+ <th>housing</th>
190
+ <th>existing_credits</th>
191
+ <th>job</th>
192
+ <th>num_dependents</th>
193
+ <th>own_telephone</th>
194
+ <th>foreign_worker</th>
195
+ </tr>
196
+ </thead>
197
+ <tbody>
198
+ <tr>
199
+ <th>0</th>
200
+ <td>male</td>
201
+ <td>'&gt;=200'</td>
202
+ <td>21</td>
203
+ <td>'critical/other existing credit'</td>
204
+ <td>education</td>
205
+ <td>2319</td>
206
+ <td>'&lt;100'</td>
207
+ <td>'&lt;1'</td>
208
+ <td>2</td>
209
+ <td>none</td>
210
+ <td>1</td>
211
+ <td>car</td>
212
+ <td>33</td>
213
+ <td>none</td>
214
+ <td>rent</td>
215
+ <td>1</td>
216
+ <td>skilled</td>
217
+ <td>1</td>
218
+ <td>none</td>
219
+ <td>yes</td>
220
+ </tr>
221
+ </tbody>
222
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
223
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
224
+ 0 & male & '>=200' & 21 & 'critical/other existing credit' & education & 2319 & '<100' & '<1' & 2 & none & 1 & car & 33 & none & rent & 1 & skilled & 1 & none & yes \\
225
+ \end{tabular}
226
+ ","{'age': 33, 'checking_status': ""'>=200'"", 'credit_amount': 2319, 'credit_history': ""'critical/other existing credit'"", 'duration': 21, 'employment': ""'<1'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'rent', 'installment_commitment': 2, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': 'education', 'residence_since': 1, 'savings_status': ""'<100'""}",A 33-year-old male German Foreigner is applying for a loan of 2319 credits for 21 months for education purposes. He has a checking account with 200 Deutsche Mark or more and a savings acccount with less than 100 Deutsche Mark. He has critical account or has other credits existing but not at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 2%. He has no other installment plans and 1 credits at this bank. He is employed for less than one years. He has lived in a rented apartment for 1 years. He owns a car. He does not own a telephone and has 1 person that he is liable to provide maintenance for.
227
+ 4,female,'no checking',12,'existing paid',radio/tv,886,'no known savings','1<=X<4',4,none,2,car,21,none,own,1,skilled,1,none,yes,good,"gender is female, checking_status is 'no checking', duration is 12, credit_history is 'existing paid', purpose is radio/tv, credit_amount is 886, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 4, other_parties is none, residence_since is 2, property_magnitude is car, age is 21, other_payment_plans is none, housing is own, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : female
228
+ - checking_status : 'no checking'
229
+ - duration : 12
230
+ - credit_history : 'existing paid'
231
+ - purpose : radio/tv
232
+ - credit_amount : 886
233
+ - savings_status : 'no known savings'
234
+ - employment : '1<=X<4'
235
+ - installment_commitment : 4
236
+ - other_parties : none
237
+ - residence_since : 2
238
+ - property_magnitude : car
239
+ - age : 21
240
+ - other_payment_plans : none
241
+ - housing : own
242
+ - existing_credits : 1
243
+ - job : skilled
244
+ - num_dependents : 1
245
+ - own_telephone : none
246
+ - foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 12. The credit_history is 'existing paid'. The purpose is radio/tv. The credit_amount is 886. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 4. The other_parties is none. The residence_since is 2. The property_magnitude is car. The age is 21. The other_payment_plans is none. The housing is own. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
247
+ <thead>
248
+ <tr style=""text-align: right;"">
249
+ <th></th>
250
+ <th>gender</th>
251
+ <th>checking_status</th>
252
+ <th>duration</th>
253
+ <th>credit_history</th>
254
+ <th>purpose</th>
255
+ <th>credit_amount</th>
256
+ <th>savings_status</th>
257
+ <th>employment</th>
258
+ <th>installment_commitment</th>
259
+ <th>other_parties</th>
260
+ <th>residence_since</th>
261
+ <th>property_magnitude</th>
262
+ <th>age</th>
263
+ <th>other_payment_plans</th>
264
+ <th>housing</th>
265
+ <th>existing_credits</th>
266
+ <th>job</th>
267
+ <th>num_dependents</th>
268
+ <th>own_telephone</th>
269
+ <th>foreign_worker</th>
270
+ </tr>
271
+ </thead>
272
+ <tbody>
273
+ <tr>
274
+ <th>0</th>
275
+ <td>female</td>
276
+ <td>'no checking'</td>
277
+ <td>12</td>
278
+ <td>'existing paid'</td>
279
+ <td>radio/tv</td>
280
+ <td>886</td>
281
+ <td>'no known savings'</td>
282
+ <td>'1&lt;=X&lt;4'</td>
283
+ <td>4</td>
284
+ <td>none</td>
285
+ <td>2</td>
286
+ <td>car</td>
287
+ <td>21</td>
288
+ <td>none</td>
289
+ <td>own</td>
290
+ <td>1</td>
291
+ <td>skilled</td>
292
+ <td>1</td>
293
+ <td>none</td>
294
+ <td>yes</td>
295
+ </tr>
296
+ </tbody>
297
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
298
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
299
+ 0 & female & 'no checking' & 12 & 'existing paid' & radio/tv & 886 & 'no known savings' & '1<=X<4' & 4 & none & 2 & car & 21 & none & own & 1 & skilled & 1 & none & yes \\
300
+ \end{tabular}
301
+ ","{'age': 21, 'checking_status': ""'no checking'"", 'credit_amount': 886, 'credit_history': ""'existing paid'"", 'duration': 12, 'employment': ""'1<=X<4'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 4, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': 'radio/tv', 'residence_since': 2, 'savings_status': ""'no known savings'""}",A 21-year-old female German Foreigner is applying for a loan of 886 credits for 12 months for radio or tv purposes. She has no checking account and no known savings. She has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 1 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 2 years. She owns a car. She does not own a telephone and has 1 person that she is liable to provide maintenance for.
302
+ 2,male,'no checking',6,'existing paid','used car',1236,'500<=X<1000','1<=X<4',2,none,4,'life insurance',50,none,rent,1,skilled,1,none,yes,good,"gender is male, checking_status is 'no checking', duration is 6, credit_history is 'existing paid', purpose is 'used car', credit_amount is 1236, savings_status is '500<=X<1000', employment is '1<=X<4', installment_commitment is 2, other_parties is none, residence_since is 4, property_magnitude is 'life insurance', age is 50, other_payment_plans is none, housing is rent, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : male
303
+ - checking_status : 'no checking'
304
+ - duration : 6
305
+ - credit_history : 'existing paid'
306
+ - purpose : 'used car'
307
+ - credit_amount : 1236
308
+ - savings_status : '500<=X<1000'
309
+ - employment : '1<=X<4'
310
+ - installment_commitment : 2
311
+ - other_parties : none
312
+ - residence_since : 4
313
+ - property_magnitude : 'life insurance'
314
+ - age : 50
315
+ - other_payment_plans : none
316
+ - housing : rent
317
+ - existing_credits : 1
318
+ - job : skilled
319
+ - num_dependents : 1
320
+ - own_telephone : none
321
+ - foreign_worker : yes",The gender is male. The checking_status is 'no checking'. The duration is 6. The credit_history is 'existing paid'. The purpose is 'used car'. The credit_amount is 1236. The savings_status is '500<=X<1000'. The employment is '1<=X<4'. The installment_commitment is 2. The other_parties is none. The residence_since is 4. The property_magnitude is 'life insurance'. The age is 50. The other_payment_plans is none. The housing is rent. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
322
+ <thead>
323
+ <tr style=""text-align: right;"">
324
+ <th></th>
325
+ <th>gender</th>
326
+ <th>checking_status</th>
327
+ <th>duration</th>
328
+ <th>credit_history</th>
329
+ <th>purpose</th>
330
+ <th>credit_amount</th>
331
+ <th>savings_status</th>
332
+ <th>employment</th>
333
+ <th>installment_commitment</th>
334
+ <th>other_parties</th>
335
+ <th>residence_since</th>
336
+ <th>property_magnitude</th>
337
+ <th>age</th>
338
+ <th>other_payment_plans</th>
339
+ <th>housing</th>
340
+ <th>existing_credits</th>
341
+ <th>job</th>
342
+ <th>num_dependents</th>
343
+ <th>own_telephone</th>
344
+ <th>foreign_worker</th>
345
+ </tr>
346
+ </thead>
347
+ <tbody>
348
+ <tr>
349
+ <th>0</th>
350
+ <td>male</td>
351
+ <td>'no checking'</td>
352
+ <td>6</td>
353
+ <td>'existing paid'</td>
354
+ <td>'used car'</td>
355
+ <td>1236</td>
356
+ <td>'500&lt;=X&lt;1000'</td>
357
+ <td>'1&lt;=X&lt;4'</td>
358
+ <td>2</td>
359
+ <td>none</td>
360
+ <td>4</td>
361
+ <td>'life insurance'</td>
362
+ <td>50</td>
363
+ <td>none</td>
364
+ <td>rent</td>
365
+ <td>1</td>
366
+ <td>skilled</td>
367
+ <td>1</td>
368
+ <td>none</td>
369
+ <td>yes</td>
370
+ </tr>
371
+ </tbody>
372
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
373
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
374
+ 0 & male & 'no checking' & 6 & 'existing paid' & 'used car' & 1236 & '500<=X<1000' & '1<=X<4' & 2 & none & 4 & 'life insurance' & 50 & none & rent & 1 & skilled & 1 & none & yes \\
375
+ \end{tabular}
376
+ ","{'age': 50, 'checking_status': ""'no checking'"", 'credit_amount': 1236, 'credit_history': ""'existing paid'"", 'duration': 6, 'employment': ""'1<=X<4'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'rent', 'installment_commitment': 2, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': ""'life insurance'"", 'purpose': ""'used car'"", 'residence_since': 4, 'savings_status': ""'500<=X<1000'""}",A 50-year-old male German Foreigner is applying for a loan of 1236 credits for 6 months for used car purposes. He has no checking account and a savings with more than 500 Deutsche Mark but less than 1000 Deutsche Mark. He has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 2%. He has no other installment plans and 1 credits at this bank. He is employed for more than one year but less than four years. He has lived in a rented apartment for 4 years. He owns life insurance property. He does not own a telephone and has 1 person that he is liable to provide maintenance for.
377
+ 5,female,'<0',24,'existing paid','new car',1442,'<100','4<=X<7',4,none,4,car,23,none,rent,2,skilled,1,none,yes,bad,"gender is female, checking_status is '<0', duration is 24, credit_history is 'existing paid', purpose is 'new car', credit_amount is 1442, savings_status is '<100', employment is '4<=X<7', installment_commitment is 4, other_parties is none, residence_since is 4, property_magnitude is car, age is 23, other_payment_plans is none, housing is rent, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : female
378
+ - checking_status : '<0'
379
+ - duration : 24
380
+ - credit_history : 'existing paid'
381
+ - purpose : 'new car'
382
+ - credit_amount : 1442
383
+ - savings_status : '<100'
384
+ - employment : '4<=X<7'
385
+ - installment_commitment : 4
386
+ - other_parties : none
387
+ - residence_since : 4
388
+ - property_magnitude : car
389
+ - age : 23
390
+ - other_payment_plans : none
391
+ - housing : rent
392
+ - existing_credits : 2
393
+ - job : skilled
394
+ - num_dependents : 1
395
+ - own_telephone : none
396
+ - foreign_worker : yes",The gender is female. The checking_status is '<0'. The duration is 24. The credit_history is 'existing paid'. The purpose is 'new car'. The credit_amount is 1442. The savings_status is '<100'. The employment is '4<=X<7'. The installment_commitment is 4. The other_parties is none. The residence_since is 4. The property_magnitude is car. The age is 23. The other_payment_plans is none. The housing is rent. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
397
+ <thead>
398
+ <tr style=""text-align: right;"">
399
+ <th></th>
400
+ <th>gender</th>
401
+ <th>checking_status</th>
402
+ <th>duration</th>
403
+ <th>credit_history</th>
404
+ <th>purpose</th>
405
+ <th>credit_amount</th>
406
+ <th>savings_status</th>
407
+ <th>employment</th>
408
+ <th>installment_commitment</th>
409
+ <th>other_parties</th>
410
+ <th>residence_since</th>
411
+ <th>property_magnitude</th>
412
+ <th>age</th>
413
+ <th>other_payment_plans</th>
414
+ <th>housing</th>
415
+ <th>existing_credits</th>
416
+ <th>job</th>
417
+ <th>num_dependents</th>
418
+ <th>own_telephone</th>
419
+ <th>foreign_worker</th>
420
+ </tr>
421
+ </thead>
422
+ <tbody>
423
+ <tr>
424
+ <th>0</th>
425
+ <td>female</td>
426
+ <td>'&lt;0'</td>
427
+ <td>24</td>
428
+ <td>'existing paid'</td>
429
+ <td>'new car'</td>
430
+ <td>1442</td>
431
+ <td>'&lt;100'</td>
432
+ <td>'4&lt;=X&lt;7'</td>
433
+ <td>4</td>
434
+ <td>none</td>
435
+ <td>4</td>
436
+ <td>car</td>
437
+ <td>23</td>
438
+ <td>none</td>
439
+ <td>rent</td>
440
+ <td>2</td>
441
+ <td>skilled</td>
442
+ <td>1</td>
443
+ <td>none</td>
444
+ <td>yes</td>
445
+ </tr>
446
+ </tbody>
447
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
448
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
449
+ 0 & female & '<0' & 24 & 'existing paid' & 'new car' & 1442 & '<100' & '4<=X<7' & 4 & none & 4 & car & 23 & none & rent & 2 & skilled & 1 & none & yes \\
450
+ \end{tabular}
451
+ ","{'age': 23, 'checking_status': ""'<0'"", 'credit_amount': 1442, 'credit_history': ""'existing paid'"", 'duration': 24, 'employment': ""'4<=X<7'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'rent', 'installment_commitment': 4, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': ""'new car'"", 'residence_since': 4, 'savings_status': ""'<100'""}",A 23-year-old female German Foreigner is applying for a loan of 1442 credits for 24 months for new car purposes. She has a checking account with 0 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. She has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 2 credits at this bank. She is employed for more than four years but less than seven years. She has lived in a rented apartment for 4 years. She owns a car. She does not own a telephone and has 1 person that she is liable to provide maintenance for.
452
+ 6,male,'no checking',6,'existing paid',furniture/equipment,2978,'500<=X<1000','1<=X<4',1,none,2,car,32,none,own,1,skilled,1,yes,yes,good,"gender is male, checking_status is 'no checking', duration is 6, credit_history is 'existing paid', purpose is furniture/equipment, credit_amount is 2978, savings_status is '500<=X<1000', employment is '1<=X<4', installment_commitment is 1, other_parties is none, residence_since is 2, property_magnitude is car, age is 32, other_payment_plans is none, housing is own, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : male
453
+ - checking_status : 'no checking'
454
+ - duration : 6
455
+ - credit_history : 'existing paid'
456
+ - purpose : furniture/equipment
457
+ - credit_amount : 2978
458
+ - savings_status : '500<=X<1000'
459
+ - employment : '1<=X<4'
460
+ - installment_commitment : 1
461
+ - other_parties : none
462
+ - residence_since : 2
463
+ - property_magnitude : car
464
+ - age : 32
465
+ - other_payment_plans : none
466
+ - housing : own
467
+ - existing_credits : 1
468
+ - job : skilled
469
+ - num_dependents : 1
470
+ - own_telephone : yes
471
+ - foreign_worker : yes",The gender is male. The checking_status is 'no checking'. The duration is 6. The credit_history is 'existing paid'. The purpose is furniture/equipment. The credit_amount is 2978. The savings_status is '500<=X<1000'. The employment is '1<=X<4'. The installment_commitment is 1. The other_parties is none. The residence_since is 2. The property_magnitude is car. The age is 32. The other_payment_plans is none. The housing is own. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
472
+ <thead>
473
+ <tr style=""text-align: right;"">
474
+ <th></th>
475
+ <th>gender</th>
476
+ <th>checking_status</th>
477
+ <th>duration</th>
478
+ <th>credit_history</th>
479
+ <th>purpose</th>
480
+ <th>credit_amount</th>
481
+ <th>savings_status</th>
482
+ <th>employment</th>
483
+ <th>installment_commitment</th>
484
+ <th>other_parties</th>
485
+ <th>residence_since</th>
486
+ <th>property_magnitude</th>
487
+ <th>age</th>
488
+ <th>other_payment_plans</th>
489
+ <th>housing</th>
490
+ <th>existing_credits</th>
491
+ <th>job</th>
492
+ <th>num_dependents</th>
493
+ <th>own_telephone</th>
494
+ <th>foreign_worker</th>
495
+ </tr>
496
+ </thead>
497
+ <tbody>
498
+ <tr>
499
+ <th>0</th>
500
+ <td>male</td>
501
+ <td>'no checking'</td>
502
+ <td>6</td>
503
+ <td>'existing paid'</td>
504
+ <td>furniture/equipment</td>
505
+ <td>2978</td>
506
+ <td>'500&lt;=X&lt;1000'</td>
507
+ <td>'1&lt;=X&lt;4'</td>
508
+ <td>1</td>
509
+ <td>none</td>
510
+ <td>2</td>
511
+ <td>car</td>
512
+ <td>32</td>
513
+ <td>none</td>
514
+ <td>own</td>
515
+ <td>1</td>
516
+ <td>skilled</td>
517
+ <td>1</td>
518
+ <td>yes</td>
519
+ <td>yes</td>
520
+ </tr>
521
+ </tbody>
522
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
523
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
524
+ 0 & male & 'no checking' & 6 & 'existing paid' & furniture/equipment & 2978 & '500<=X<1000' & '1<=X<4' & 1 & none & 2 & car & 32 & none & own & 1 & skilled & 1 & yes & yes \\
525
+ \end{tabular}
526
+ ","{'age': 32, 'checking_status': ""'no checking'"", 'credit_amount': 2978, 'credit_history': ""'existing paid'"", 'duration': 6, 'employment': ""'1<=X<4'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'own', 'installment_commitment': 1, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'yes', 'property_magnitude': 'car', 'purpose': 'furniture/equipment', 'residence_since': 2, 'savings_status': ""'500<=X<1000'""}",A 32-year-old male German Foreigner is applying for a loan of 2978 credits for 6 months for furniture or equipment purposes. He has no checking account and a savings with more than 500 Deutsche Mark but less than 1000 Deutsche Mark. He has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 1%. He has no other installment plans and 1 credits at this bank. He is employed for more than one year but less than four years. He has lived in a self-owned house for 2 years. He owns a car. He owns a telephone and has 1 person that he is liable to provide maintenance for.
527
+ 11,female,'0<=X<200',36,'existing paid',radio/tv,4795,'<100','<1',4,none,1,'no known property',30,none,own,1,'high qualif/self emp/mgmt',1,yes,yes,good,"gender is female, checking_status is '0<=X<200', duration is 36, credit_history is 'existing paid', purpose is radio/tv, credit_amount is 4795, savings_status is '<100', employment is '<1', installment_commitment is 4, other_parties is none, residence_since is 1, property_magnitude is 'no known property', age is 30, other_payment_plans is none, housing is own, existing_credits is 1, job is 'high qualif/self emp/mgmt', num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : female
528
+ - checking_status : '0<=X<200'
529
+ - duration : 36
530
+ - credit_history : 'existing paid'
531
+ - purpose : radio/tv
532
+ - credit_amount : 4795
533
+ - savings_status : '<100'
534
+ - employment : '<1'
535
+ - installment_commitment : 4
536
+ - other_parties : none
537
+ - residence_since : 1
538
+ - property_magnitude : 'no known property'
539
+ - age : 30
540
+ - other_payment_plans : none
541
+ - housing : own
542
+ - existing_credits : 1
543
+ - job : 'high qualif/self emp/mgmt'
544
+ - num_dependents : 1
545
+ - own_telephone : yes
546
+ - foreign_worker : yes",The gender is female. The checking_status is '0<=X<200'. The duration is 36. The credit_history is 'existing paid'. The purpose is radio/tv. The credit_amount is 4795. The savings_status is '<100'. The employment is '<1'. The installment_commitment is 4. The other_parties is none. The residence_since is 1. The property_magnitude is 'no known property'. The age is 30. The other_payment_plans is none. The housing is own. The existing_credits is 1. The job is 'high qualif/self emp/mgmt'. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
547
+ <thead>
548
+ <tr style=""text-align: right;"">
549
+ <th></th>
550
+ <th>gender</th>
551
+ <th>checking_status</th>
552
+ <th>duration</th>
553
+ <th>credit_history</th>
554
+ <th>purpose</th>
555
+ <th>credit_amount</th>
556
+ <th>savings_status</th>
557
+ <th>employment</th>
558
+ <th>installment_commitment</th>
559
+ <th>other_parties</th>
560
+ <th>residence_since</th>
561
+ <th>property_magnitude</th>
562
+ <th>age</th>
563
+ <th>other_payment_plans</th>
564
+ <th>housing</th>
565
+ <th>existing_credits</th>
566
+ <th>job</th>
567
+ <th>num_dependents</th>
568
+ <th>own_telephone</th>
569
+ <th>foreign_worker</th>
570
+ </tr>
571
+ </thead>
572
+ <tbody>
573
+ <tr>
574
+ <th>0</th>
575
+ <td>female</td>
576
+ <td>'0&lt;=X&lt;200'</td>
577
+ <td>36</td>
578
+ <td>'existing paid'</td>
579
+ <td>radio/tv</td>
580
+ <td>4795</td>
581
+ <td>'&lt;100'</td>
582
+ <td>'&lt;1'</td>
583
+ <td>4</td>
584
+ <td>none</td>
585
+ <td>1</td>
586
+ <td>'no known property'</td>
587
+ <td>30</td>
588
+ <td>none</td>
589
+ <td>own</td>
590
+ <td>1</td>
591
+ <td>'high qualif/self emp/mgmt'</td>
592
+ <td>1</td>
593
+ <td>yes</td>
594
+ <td>yes</td>
595
+ </tr>
596
+ </tbody>
597
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
598
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
599
+ 0 & female & '0<=X<200' & 36 & 'existing paid' & radio/tv & 4795 & '<100' & '<1' & 4 & none & 1 & 'no known property' & 30 & none & own & 1 & 'high qualif/self emp/mgmt' & 1 & yes & yes \\
600
+ \end{tabular}
601
+ ","{'age': 30, 'checking_status': ""'0<=X<200'"", 'credit_amount': 4795, 'credit_history': ""'existing paid'"", 'duration': 36, 'employment': ""'<1'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 4, 'job': ""'high qualif/self emp/mgmt'"", 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'yes', 'property_magnitude': ""'no known property'"", 'purpose': 'radio/tv', 'residence_since': 1, 'savings_status': ""'<100'""}",A 30-year-old female German Foreigner is applying for a loan of 4795 credits for 36 months for radio or tv purposes. She has a checking account with less than 200 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. She has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 1 credits at this bank. She is employed for less than one years and is recognized as a highly qualified employee or is self employed or has managerial position. She has lived in a self-owned house for 1 years. She owns no known property. She owns a telephone and has 1 person that she is liable to provide maintenance for.
new_data/german-fewshot.csv ADDED
@@ -0,0 +1,751 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Unnamed: 0,gender,checking_status,duration,credit_history,purpose,credit_amount,savings_status,employment,installment_commitment,other_parties,residence_since,property_magnitude,age,other_payment_plans,housing,existing_credits,job,num_dependents,own_telephone,foreign_worker,class,great,list,text,html,latex,json,LIFT
2
+ 0,male,'<0',60,'delayed previously',business,6836,'<100','>=7',3,none,4,'no known property',63,none,own,2,skilled,1,yes,yes,bad,"gender is male, checking_status is '<0', duration is 60, credit_history is 'delayed previously', purpose is business, credit_amount is 6836, savings_status is '<100', employment is '>=7', installment_commitment is 3, other_parties is none, residence_since is 4, property_magnitude is 'no known property', age is 63, other_payment_plans is none, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : male
3
+ - checking_status : '<0'
4
+ - duration : 60
5
+ - credit_history : 'delayed previously'
6
+ - purpose : business
7
+ - credit_amount : 6836
8
+ - savings_status : '<100'
9
+ - employment : '>=7'
10
+ - installment_commitment : 3
11
+ - other_parties : none
12
+ - residence_since : 4
13
+ - property_magnitude : 'no known property'
14
+ - age : 63
15
+ - other_payment_plans : none
16
+ - housing : own
17
+ - existing_credits : 2
18
+ - job : skilled
19
+ - num_dependents : 1
20
+ - own_telephone : yes
21
+ - foreign_worker : yes",The gender is male. The checking_status is '<0'. The duration is 60. The credit_history is 'delayed previously'. The purpose is business. The credit_amount is 6836. The savings_status is '<100'. The employment is '>=7'. The installment_commitment is 3. The other_parties is none. The residence_since is 4. The property_magnitude is 'no known property'. The age is 63. The other_payment_plans is none. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
22
+ <thead>
23
+ <tr style=""text-align: right;"">
24
+ <th></th>
25
+ <th>gender</th>
26
+ <th>checking_status</th>
27
+ <th>duration</th>
28
+ <th>credit_history</th>
29
+ <th>purpose</th>
30
+ <th>credit_amount</th>
31
+ <th>savings_status</th>
32
+ <th>employment</th>
33
+ <th>installment_commitment</th>
34
+ <th>other_parties</th>
35
+ <th>residence_since</th>
36
+ <th>property_magnitude</th>
37
+ <th>age</th>
38
+ <th>other_payment_plans</th>
39
+ <th>housing</th>
40
+ <th>existing_credits</th>
41
+ <th>job</th>
42
+ <th>num_dependents</th>
43
+ <th>own_telephone</th>
44
+ <th>foreign_worker</th>
45
+ </tr>
46
+ </thead>
47
+ <tbody>
48
+ <tr>
49
+ <th>0</th>
50
+ <td>male</td>
51
+ <td>'&lt;0'</td>
52
+ <td>60</td>
53
+ <td>'delayed previously'</td>
54
+ <td>business</td>
55
+ <td>6836</td>
56
+ <td>'&lt;100'</td>
57
+ <td>'&gt;=7'</td>
58
+ <td>3</td>
59
+ <td>none</td>
60
+ <td>4</td>
61
+ <td>'no known property'</td>
62
+ <td>63</td>
63
+ <td>none</td>
64
+ <td>own</td>
65
+ <td>2</td>
66
+ <td>skilled</td>
67
+ <td>1</td>
68
+ <td>yes</td>
69
+ <td>yes</td>
70
+ </tr>
71
+ </tbody>
72
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
73
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
74
+ 0 & male & '<0' & 60 & 'delayed previously' & business & 6836 & '<100' & '>=7' & 3 & none & 4 & 'no known property' & 63 & none & own & 2 & skilled & 1 & yes & yes \\
75
+ \end{tabular}
76
+ ","{'age': 63, 'checking_status': ""'<0'"", 'credit_amount': 6836, 'credit_history': ""'delayed previously'"", 'duration': 60, 'employment': ""'>=7'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'own', 'installment_commitment': 3, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'yes', 'property_magnitude': ""'no known property'"", 'purpose': 'business', 'residence_since': 4, 'savings_status': ""'<100'""}",A 63-year-old male German Foreigner is applying for a loan of 6836 credits for 60 months for business purposes. He has a checking account with 0 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. He has delayed paying back credits received from this bank in the past. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 3%. He has no other installment plans and 2 credits at this bank. He is employed for more than seven years. He has lived in a self-owned house for 4 years. He owns no known property. He owns a telephone and has 1 person that he is liable to provide maintenance for.
77
+ 3,female,'no checking',21,'no credits/all paid','new car',5003,'no known savings','1<=X<4',1,none,4,'life insurance',29,bank,own,2,skilled,1,yes,yes,bad,"gender is female, checking_status is 'no checking', duration is 21, credit_history is 'no credits/all paid', purpose is 'new car', credit_amount is 5003, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 1, other_parties is none, residence_since is 4, property_magnitude is 'life insurance', age is 29, other_payment_plans is bank, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : female
78
+ - checking_status : 'no checking'
79
+ - duration : 21
80
+ - credit_history : 'no credits/all paid'
81
+ - purpose : 'new car'
82
+ - credit_amount : 5003
83
+ - savings_status : 'no known savings'
84
+ - employment : '1<=X<4'
85
+ - installment_commitment : 1
86
+ - other_parties : none
87
+ - residence_since : 4
88
+ - property_magnitude : 'life insurance'
89
+ - age : 29
90
+ - other_payment_plans : bank
91
+ - housing : own
92
+ - existing_credits : 2
93
+ - job : skilled
94
+ - num_dependents : 1
95
+ - own_telephone : yes
96
+ - foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 21. The credit_history is 'no credits/all paid'. The purpose is 'new car'. The credit_amount is 5003. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 1. The other_parties is none. The residence_since is 4. The property_magnitude is 'life insurance'. The age is 29. The other_payment_plans is bank. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
97
+ <thead>
98
+ <tr style=""text-align: right;"">
99
+ <th></th>
100
+ <th>gender</th>
101
+ <th>checking_status</th>
102
+ <th>duration</th>
103
+ <th>credit_history</th>
104
+ <th>purpose</th>
105
+ <th>credit_amount</th>
106
+ <th>savings_status</th>
107
+ <th>employment</th>
108
+ <th>installment_commitment</th>
109
+ <th>other_parties</th>
110
+ <th>residence_since</th>
111
+ <th>property_magnitude</th>
112
+ <th>age</th>
113
+ <th>other_payment_plans</th>
114
+ <th>housing</th>
115
+ <th>existing_credits</th>
116
+ <th>job</th>
117
+ <th>num_dependents</th>
118
+ <th>own_telephone</th>
119
+ <th>foreign_worker</th>
120
+ </tr>
121
+ </thead>
122
+ <tbody>
123
+ <tr>
124
+ <th>0</th>
125
+ <td>female</td>
126
+ <td>'no checking'</td>
127
+ <td>21</td>
128
+ <td>'no credits/all paid'</td>
129
+ <td>'new car'</td>
130
+ <td>5003</td>
131
+ <td>'no known savings'</td>
132
+ <td>'1&lt;=X&lt;4'</td>
133
+ <td>1</td>
134
+ <td>none</td>
135
+ <td>4</td>
136
+ <td>'life insurance'</td>
137
+ <td>29</td>
138
+ <td>bank</td>
139
+ <td>own</td>
140
+ <td>2</td>
141
+ <td>skilled</td>
142
+ <td>1</td>
143
+ <td>yes</td>
144
+ <td>yes</td>
145
+ </tr>
146
+ </tbody>
147
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
148
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
149
+ 0 & female & 'no checking' & 21 & 'no credits/all paid' & 'new car' & 5003 & 'no known savings' & '1<=X<4' & 1 & none & 4 & 'life insurance' & 29 & bank & own & 2 & skilled & 1 & yes & yes \\
150
+ \end{tabular}
151
+ ","{'age': 29, 'checking_status': ""'no checking'"", 'credit_amount': 5003, 'credit_history': ""'no credits/all paid'"", 'duration': 21, 'employment': ""'1<=X<4'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 1, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'bank', 'own_telephone': 'yes', 'property_magnitude': ""'life insurance'"", 'purpose': ""'new car'"", 'residence_since': 4, 'savings_status': ""'no known savings'""}",A 29-year-old female German Foreigner is applying for a loan of 5003 credits for 21 months for new car purposes. She has no checking account and no known savings. She did not take any credits at this bank or has duly paid back all credits at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 1%. She has other installment plans with a bank and 2 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 4 years. She owns life insurance property. She owns a telephone and has 1 person that she is liable to provide maintenance for.
152
+ 1,male,'>=200',21,'critical/other existing credit',education,2319,'<100','<1',2,none,1,car,33,none,rent,1,skilled,1,none,yes,bad,"gender is male, checking_status is '>=200', duration is 21, credit_history is 'critical/other existing credit', purpose is education, credit_amount is 2319, savings_status is '<100', employment is '<1', installment_commitment is 2, other_parties is none, residence_since is 1, property_magnitude is car, age is 33, other_payment_plans is none, housing is rent, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : male
153
+ - checking_status : '>=200'
154
+ - duration : 21
155
+ - credit_history : 'critical/other existing credit'
156
+ - purpose : education
157
+ - credit_amount : 2319
158
+ - savings_status : '<100'
159
+ - employment : '<1'
160
+ - installment_commitment : 2
161
+ - other_parties : none
162
+ - residence_since : 1
163
+ - property_magnitude : car
164
+ - age : 33
165
+ - other_payment_plans : none
166
+ - housing : rent
167
+ - existing_credits : 1
168
+ - job : skilled
169
+ - num_dependents : 1
170
+ - own_telephone : none
171
+ - foreign_worker : yes",The gender is male. The checking_status is '>=200'. The duration is 21. The credit_history is 'critical/other existing credit'. The purpose is education. The credit_amount is 2319. The savings_status is '<100'. The employment is '<1'. The installment_commitment is 2. The other_parties is none. The residence_since is 1. The property_magnitude is car. The age is 33. The other_payment_plans is none. The housing is rent. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
172
+ <thead>
173
+ <tr style=""text-align: right;"">
174
+ <th></th>
175
+ <th>gender</th>
176
+ <th>checking_status</th>
177
+ <th>duration</th>
178
+ <th>credit_history</th>
179
+ <th>purpose</th>
180
+ <th>credit_amount</th>
181
+ <th>savings_status</th>
182
+ <th>employment</th>
183
+ <th>installment_commitment</th>
184
+ <th>other_parties</th>
185
+ <th>residence_since</th>
186
+ <th>property_magnitude</th>
187
+ <th>age</th>
188
+ <th>other_payment_plans</th>
189
+ <th>housing</th>
190
+ <th>existing_credits</th>
191
+ <th>job</th>
192
+ <th>num_dependents</th>
193
+ <th>own_telephone</th>
194
+ <th>foreign_worker</th>
195
+ </tr>
196
+ </thead>
197
+ <tbody>
198
+ <tr>
199
+ <th>0</th>
200
+ <td>male</td>
201
+ <td>'&gt;=200'</td>
202
+ <td>21</td>
203
+ <td>'critical/other existing credit'</td>
204
+ <td>education</td>
205
+ <td>2319</td>
206
+ <td>'&lt;100'</td>
207
+ <td>'&lt;1'</td>
208
+ <td>2</td>
209
+ <td>none</td>
210
+ <td>1</td>
211
+ <td>car</td>
212
+ <td>33</td>
213
+ <td>none</td>
214
+ <td>rent</td>
215
+ <td>1</td>
216
+ <td>skilled</td>
217
+ <td>1</td>
218
+ <td>none</td>
219
+ <td>yes</td>
220
+ </tr>
221
+ </tbody>
222
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
223
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
224
+ 0 & male & '>=200' & 21 & 'critical/other existing credit' & education & 2319 & '<100' & '<1' & 2 & none & 1 & car & 33 & none & rent & 1 & skilled & 1 & none & yes \\
225
+ \end{tabular}
226
+ ","{'age': 33, 'checking_status': ""'>=200'"", 'credit_amount': 2319, 'credit_history': ""'critical/other existing credit'"", 'duration': 21, 'employment': ""'<1'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'rent', 'installment_commitment': 2, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': 'education', 'residence_since': 1, 'savings_status': ""'<100'""}",A 33-year-old male German Foreigner is applying for a loan of 2319 credits for 21 months for education purposes. He has a checking account with 200 Deutsche Mark or more and a savings acccount with less than 100 Deutsche Mark. He has critical account or has other credits existing but not at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 2%. He has no other installment plans and 1 credits at this bank. He is employed for less than one years. He has lived in a rented apartment for 1 years. He owns a car. He does not own a telephone and has 1 person that he is liable to provide maintenance for.
227
+ 4,female,'no checking',12,'existing paid',radio/tv,886,'no known savings','1<=X<4',4,none,2,car,21,none,own,1,skilled,1,none,yes,good,"gender is female, checking_status is 'no checking', duration is 12, credit_history is 'existing paid', purpose is radio/tv, credit_amount is 886, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 4, other_parties is none, residence_since is 2, property_magnitude is car, age is 21, other_payment_plans is none, housing is own, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : female
228
+ - checking_status : 'no checking'
229
+ - duration : 12
230
+ - credit_history : 'existing paid'
231
+ - purpose : radio/tv
232
+ - credit_amount : 886
233
+ - savings_status : 'no known savings'
234
+ - employment : '1<=X<4'
235
+ - installment_commitment : 4
236
+ - other_parties : none
237
+ - residence_since : 2
238
+ - property_magnitude : car
239
+ - age : 21
240
+ - other_payment_plans : none
241
+ - housing : own
242
+ - existing_credits : 1
243
+ - job : skilled
244
+ - num_dependents : 1
245
+ - own_telephone : none
246
+ - foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 12. The credit_history is 'existing paid'. The purpose is radio/tv. The credit_amount is 886. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 4. The other_parties is none. The residence_since is 2. The property_magnitude is car. The age is 21. The other_payment_plans is none. The housing is own. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
247
+ <thead>
248
+ <tr style=""text-align: right;"">
249
+ <th></th>
250
+ <th>gender</th>
251
+ <th>checking_status</th>
252
+ <th>duration</th>
253
+ <th>credit_history</th>
254
+ <th>purpose</th>
255
+ <th>credit_amount</th>
256
+ <th>savings_status</th>
257
+ <th>employment</th>
258
+ <th>installment_commitment</th>
259
+ <th>other_parties</th>
260
+ <th>residence_since</th>
261
+ <th>property_magnitude</th>
262
+ <th>age</th>
263
+ <th>other_payment_plans</th>
264
+ <th>housing</th>
265
+ <th>existing_credits</th>
266
+ <th>job</th>
267
+ <th>num_dependents</th>
268
+ <th>own_telephone</th>
269
+ <th>foreign_worker</th>
270
+ </tr>
271
+ </thead>
272
+ <tbody>
273
+ <tr>
274
+ <th>0</th>
275
+ <td>female</td>
276
+ <td>'no checking'</td>
277
+ <td>12</td>
278
+ <td>'existing paid'</td>
279
+ <td>radio/tv</td>
280
+ <td>886</td>
281
+ <td>'no known savings'</td>
282
+ <td>'1&lt;=X&lt;4'</td>
283
+ <td>4</td>
284
+ <td>none</td>
285
+ <td>2</td>
286
+ <td>car</td>
287
+ <td>21</td>
288
+ <td>none</td>
289
+ <td>own</td>
290
+ <td>1</td>
291
+ <td>skilled</td>
292
+ <td>1</td>
293
+ <td>none</td>
294
+ <td>yes</td>
295
+ </tr>
296
+ </tbody>
297
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
298
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
299
+ 0 & female & 'no checking' & 12 & 'existing paid' & radio/tv & 886 & 'no known savings' & '1<=X<4' & 4 & none & 2 & car & 21 & none & own & 1 & skilled & 1 & none & yes \\
300
+ \end{tabular}
301
+ ","{'age': 21, 'checking_status': ""'no checking'"", 'credit_amount': 886, 'credit_history': ""'existing paid'"", 'duration': 12, 'employment': ""'1<=X<4'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 4, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': 'radio/tv', 'residence_since': 2, 'savings_status': ""'no known savings'""}",A 21-year-old female German Foreigner is applying for a loan of 886 credits for 12 months for radio or tv purposes. She has no checking account and no known savings. She has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 1 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 2 years. She owns a car. She does not own a telephone and has 1 person that she is liable to provide maintenance for.
302
+ 2,male,'no checking',6,'existing paid','used car',1236,'500<=X<1000','1<=X<4',2,none,4,'life insurance',50,none,rent,1,skilled,1,none,yes,good,"gender is male, checking_status is 'no checking', duration is 6, credit_history is 'existing paid', purpose is 'used car', credit_amount is 1236, savings_status is '500<=X<1000', employment is '1<=X<4', installment_commitment is 2, other_parties is none, residence_since is 4, property_magnitude is 'life insurance', age is 50, other_payment_plans is none, housing is rent, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : male
303
+ - checking_status : 'no checking'
304
+ - duration : 6
305
+ - credit_history : 'existing paid'
306
+ - purpose : 'used car'
307
+ - credit_amount : 1236
308
+ - savings_status : '500<=X<1000'
309
+ - employment : '1<=X<4'
310
+ - installment_commitment : 2
311
+ - other_parties : none
312
+ - residence_since : 4
313
+ - property_magnitude : 'life insurance'
314
+ - age : 50
315
+ - other_payment_plans : none
316
+ - housing : rent
317
+ - existing_credits : 1
318
+ - job : skilled
319
+ - num_dependents : 1
320
+ - own_telephone : none
321
+ - foreign_worker : yes",The gender is male. The checking_status is 'no checking'. The duration is 6. The credit_history is 'existing paid'. The purpose is 'used car'. The credit_amount is 1236. The savings_status is '500<=X<1000'. The employment is '1<=X<4'. The installment_commitment is 2. The other_parties is none. The residence_since is 4. The property_magnitude is 'life insurance'. The age is 50. The other_payment_plans is none. The housing is rent. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
322
+ <thead>
323
+ <tr style=""text-align: right;"">
324
+ <th></th>
325
+ <th>gender</th>
326
+ <th>checking_status</th>
327
+ <th>duration</th>
328
+ <th>credit_history</th>
329
+ <th>purpose</th>
330
+ <th>credit_amount</th>
331
+ <th>savings_status</th>
332
+ <th>employment</th>
333
+ <th>installment_commitment</th>
334
+ <th>other_parties</th>
335
+ <th>residence_since</th>
336
+ <th>property_magnitude</th>
337
+ <th>age</th>
338
+ <th>other_payment_plans</th>
339
+ <th>housing</th>
340
+ <th>existing_credits</th>
341
+ <th>job</th>
342
+ <th>num_dependents</th>
343
+ <th>own_telephone</th>
344
+ <th>foreign_worker</th>
345
+ </tr>
346
+ </thead>
347
+ <tbody>
348
+ <tr>
349
+ <th>0</th>
350
+ <td>male</td>
351
+ <td>'no checking'</td>
352
+ <td>6</td>
353
+ <td>'existing paid'</td>
354
+ <td>'used car'</td>
355
+ <td>1236</td>
356
+ <td>'500&lt;=X&lt;1000'</td>
357
+ <td>'1&lt;=X&lt;4'</td>
358
+ <td>2</td>
359
+ <td>none</td>
360
+ <td>4</td>
361
+ <td>'life insurance'</td>
362
+ <td>50</td>
363
+ <td>none</td>
364
+ <td>rent</td>
365
+ <td>1</td>
366
+ <td>skilled</td>
367
+ <td>1</td>
368
+ <td>none</td>
369
+ <td>yes</td>
370
+ </tr>
371
+ </tbody>
372
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
373
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
374
+ 0 & male & 'no checking' & 6 & 'existing paid' & 'used car' & 1236 & '500<=X<1000' & '1<=X<4' & 2 & none & 4 & 'life insurance' & 50 & none & rent & 1 & skilled & 1 & none & yes \\
375
+ \end{tabular}
376
+ ","{'age': 50, 'checking_status': ""'no checking'"", 'credit_amount': 1236, 'credit_history': ""'existing paid'"", 'duration': 6, 'employment': ""'1<=X<4'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'rent', 'installment_commitment': 2, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': ""'life insurance'"", 'purpose': ""'used car'"", 'residence_since': 4, 'savings_status': ""'500<=X<1000'""}",A 50-year-old male German Foreigner is applying for a loan of 1236 credits for 6 months for used car purposes. He has no checking account and a savings with more than 500 Deutsche Mark but less than 1000 Deutsche Mark. He has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 2%. He has no other installment plans and 1 credits at this bank. He is employed for more than one year but less than four years. He has lived in a rented apartment for 4 years. He owns life insurance property. He does not own a telephone and has 1 person that he is liable to provide maintenance for.
377
+ 5,female,'<0',24,'existing paid','new car',1442,'<100','4<=X<7',4,none,4,car,23,none,rent,2,skilled,1,none,yes,bad,"gender is female, checking_status is '<0', duration is 24, credit_history is 'existing paid', purpose is 'new car', credit_amount is 1442, savings_status is '<100', employment is '4<=X<7', installment_commitment is 4, other_parties is none, residence_since is 4, property_magnitude is car, age is 23, other_payment_plans is none, housing is rent, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : female
378
+ - checking_status : '<0'
379
+ - duration : 24
380
+ - credit_history : 'existing paid'
381
+ - purpose : 'new car'
382
+ - credit_amount : 1442
383
+ - savings_status : '<100'
384
+ - employment : '4<=X<7'
385
+ - installment_commitment : 4
386
+ - other_parties : none
387
+ - residence_since : 4
388
+ - property_magnitude : car
389
+ - age : 23
390
+ - other_payment_plans : none
391
+ - housing : rent
392
+ - existing_credits : 2
393
+ - job : skilled
394
+ - num_dependents : 1
395
+ - own_telephone : none
396
+ - foreign_worker : yes",The gender is female. The checking_status is '<0'. The duration is 24. The credit_history is 'existing paid'. The purpose is 'new car'. The credit_amount is 1442. The savings_status is '<100'. The employment is '4<=X<7'. The installment_commitment is 4. The other_parties is none. The residence_since is 4. The property_magnitude is car. The age is 23. The other_payment_plans is none. The housing is rent. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
397
+ <thead>
398
+ <tr style=""text-align: right;"">
399
+ <th></th>
400
+ <th>gender</th>
401
+ <th>checking_status</th>
402
+ <th>duration</th>
403
+ <th>credit_history</th>
404
+ <th>purpose</th>
405
+ <th>credit_amount</th>
406
+ <th>savings_status</th>
407
+ <th>employment</th>
408
+ <th>installment_commitment</th>
409
+ <th>other_parties</th>
410
+ <th>residence_since</th>
411
+ <th>property_magnitude</th>
412
+ <th>age</th>
413
+ <th>other_payment_plans</th>
414
+ <th>housing</th>
415
+ <th>existing_credits</th>
416
+ <th>job</th>
417
+ <th>num_dependents</th>
418
+ <th>own_telephone</th>
419
+ <th>foreign_worker</th>
420
+ </tr>
421
+ </thead>
422
+ <tbody>
423
+ <tr>
424
+ <th>0</th>
425
+ <td>female</td>
426
+ <td>'&lt;0'</td>
427
+ <td>24</td>
428
+ <td>'existing paid'</td>
429
+ <td>'new car'</td>
430
+ <td>1442</td>
431
+ <td>'&lt;100'</td>
432
+ <td>'4&lt;=X&lt;7'</td>
433
+ <td>4</td>
434
+ <td>none</td>
435
+ <td>4</td>
436
+ <td>car</td>
437
+ <td>23</td>
438
+ <td>none</td>
439
+ <td>rent</td>
440
+ <td>2</td>
441
+ <td>skilled</td>
442
+ <td>1</td>
443
+ <td>none</td>
444
+ <td>yes</td>
445
+ </tr>
446
+ </tbody>
447
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
448
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
449
+ 0 & female & '<0' & 24 & 'existing paid' & 'new car' & 1442 & '<100' & '4<=X<7' & 4 & none & 4 & car & 23 & none & rent & 2 & skilled & 1 & none & yes \\
450
+ \end{tabular}
451
+ ","{'age': 23, 'checking_status': ""'<0'"", 'credit_amount': 1442, 'credit_history': ""'existing paid'"", 'duration': 24, 'employment': ""'4<=X<7'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'rent', 'installment_commitment': 4, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': ""'new car'"", 'residence_since': 4, 'savings_status': ""'<100'""}",A 23-year-old female German Foreigner is applying for a loan of 1442 credits for 24 months for new car purposes. She has a checking account with 0 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. She has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 2 credits at this bank. She is employed for more than four years but less than seven years. She has lived in a rented apartment for 4 years. She owns a car. She does not own a telephone and has 1 person that she is liable to provide maintenance for.
452
+ 6,male,'no checking',6,'existing paid',furniture/equipment,2978,'500<=X<1000','1<=X<4',1,none,2,car,32,none,own,1,skilled,1,yes,yes,good,"gender is male, checking_status is 'no checking', duration is 6, credit_history is 'existing paid', purpose is furniture/equipment, credit_amount is 2978, savings_status is '500<=X<1000', employment is '1<=X<4', installment_commitment is 1, other_parties is none, residence_since is 2, property_magnitude is car, age is 32, other_payment_plans is none, housing is own, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : male
453
+ - checking_status : 'no checking'
454
+ - duration : 6
455
+ - credit_history : 'existing paid'
456
+ - purpose : furniture/equipment
457
+ - credit_amount : 2978
458
+ - savings_status : '500<=X<1000'
459
+ - employment : '1<=X<4'
460
+ - installment_commitment : 1
461
+ - other_parties : none
462
+ - residence_since : 2
463
+ - property_magnitude : car
464
+ - age : 32
465
+ - other_payment_plans : none
466
+ - housing : own
467
+ - existing_credits : 1
468
+ - job : skilled
469
+ - num_dependents : 1
470
+ - own_telephone : yes
471
+ - foreign_worker : yes",The gender is male. The checking_status is 'no checking'. The duration is 6. The credit_history is 'existing paid'. The purpose is furniture/equipment. The credit_amount is 2978. The savings_status is '500<=X<1000'. The employment is '1<=X<4'. The installment_commitment is 1. The other_parties is none. The residence_since is 2. The property_magnitude is car. The age is 32. The other_payment_plans is none. The housing is own. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
472
+ <thead>
473
+ <tr style=""text-align: right;"">
474
+ <th></th>
475
+ <th>gender</th>
476
+ <th>checking_status</th>
477
+ <th>duration</th>
478
+ <th>credit_history</th>
479
+ <th>purpose</th>
480
+ <th>credit_amount</th>
481
+ <th>savings_status</th>
482
+ <th>employment</th>
483
+ <th>installment_commitment</th>
484
+ <th>other_parties</th>
485
+ <th>residence_since</th>
486
+ <th>property_magnitude</th>
487
+ <th>age</th>
488
+ <th>other_payment_plans</th>
489
+ <th>housing</th>
490
+ <th>existing_credits</th>
491
+ <th>job</th>
492
+ <th>num_dependents</th>
493
+ <th>own_telephone</th>
494
+ <th>foreign_worker</th>
495
+ </tr>
496
+ </thead>
497
+ <tbody>
498
+ <tr>
499
+ <th>0</th>
500
+ <td>male</td>
501
+ <td>'no checking'</td>
502
+ <td>6</td>
503
+ <td>'existing paid'</td>
504
+ <td>furniture/equipment</td>
505
+ <td>2978</td>
506
+ <td>'500&lt;=X&lt;1000'</td>
507
+ <td>'1&lt;=X&lt;4'</td>
508
+ <td>1</td>
509
+ <td>none</td>
510
+ <td>2</td>
511
+ <td>car</td>
512
+ <td>32</td>
513
+ <td>none</td>
514
+ <td>own</td>
515
+ <td>1</td>
516
+ <td>skilled</td>
517
+ <td>1</td>
518
+ <td>yes</td>
519
+ <td>yes</td>
520
+ </tr>
521
+ </tbody>
522
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
523
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
524
+ 0 & male & 'no checking' & 6 & 'existing paid' & furniture/equipment & 2978 & '500<=X<1000' & '1<=X<4' & 1 & none & 2 & car & 32 & none & own & 1 & skilled & 1 & yes & yes \\
525
+ \end{tabular}
526
+ ","{'age': 32, 'checking_status': ""'no checking'"", 'credit_amount': 2978, 'credit_history': ""'existing paid'"", 'duration': 6, 'employment': ""'1<=X<4'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'own', 'installment_commitment': 1, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'yes', 'property_magnitude': 'car', 'purpose': 'furniture/equipment', 'residence_since': 2, 'savings_status': ""'500<=X<1000'""}",A 32-year-old male German Foreigner is applying for a loan of 2978 credits for 6 months for furniture or equipment purposes. He has no checking account and a savings with more than 500 Deutsche Mark but less than 1000 Deutsche Mark. He has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 1%. He has no other installment plans and 1 credits at this bank. He is employed for more than one year but less than four years. He has lived in a self-owned house for 2 years. He owns a car. He owns a telephone and has 1 person that he is liable to provide maintenance for.
527
+ 11,female,'0<=X<200',36,'existing paid',radio/tv,4795,'<100','<1',4,none,1,'no known property',30,none,own,1,'high qualif/self emp/mgmt',1,yes,yes,good,"gender is female, checking_status is '0<=X<200', duration is 36, credit_history is 'existing paid', purpose is radio/tv, credit_amount is 4795, savings_status is '<100', employment is '<1', installment_commitment is 4, other_parties is none, residence_since is 1, property_magnitude is 'no known property', age is 30, other_payment_plans is none, housing is own, existing_credits is 1, job is 'high qualif/self emp/mgmt', num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : female
528
+ - checking_status : '0<=X<200'
529
+ - duration : 36
530
+ - credit_history : 'existing paid'
531
+ - purpose : radio/tv
532
+ - credit_amount : 4795
533
+ - savings_status : '<100'
534
+ - employment : '<1'
535
+ - installment_commitment : 4
536
+ - other_parties : none
537
+ - residence_since : 1
538
+ - property_magnitude : 'no known property'
539
+ - age : 30
540
+ - other_payment_plans : none
541
+ - housing : own
542
+ - existing_credits : 1
543
+ - job : 'high qualif/self emp/mgmt'
544
+ - num_dependents : 1
545
+ - own_telephone : yes
546
+ - foreign_worker : yes",The gender is female. The checking_status is '0<=X<200'. The duration is 36. The credit_history is 'existing paid'. The purpose is radio/tv. The credit_amount is 4795. The savings_status is '<100'. The employment is '<1'. The installment_commitment is 4. The other_parties is none. The residence_since is 1. The property_magnitude is 'no known property'. The age is 30. The other_payment_plans is none. The housing is own. The existing_credits is 1. The job is 'high qualif/self emp/mgmt'. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
547
+ <thead>
548
+ <tr style=""text-align: right;"">
549
+ <th></th>
550
+ <th>gender</th>
551
+ <th>checking_status</th>
552
+ <th>duration</th>
553
+ <th>credit_history</th>
554
+ <th>purpose</th>
555
+ <th>credit_amount</th>
556
+ <th>savings_status</th>
557
+ <th>employment</th>
558
+ <th>installment_commitment</th>
559
+ <th>other_parties</th>
560
+ <th>residence_since</th>
561
+ <th>property_magnitude</th>
562
+ <th>age</th>
563
+ <th>other_payment_plans</th>
564
+ <th>housing</th>
565
+ <th>existing_credits</th>
566
+ <th>job</th>
567
+ <th>num_dependents</th>
568
+ <th>own_telephone</th>
569
+ <th>foreign_worker</th>
570
+ </tr>
571
+ </thead>
572
+ <tbody>
573
+ <tr>
574
+ <th>0</th>
575
+ <td>female</td>
576
+ <td>'0&lt;=X&lt;200'</td>
577
+ <td>36</td>
578
+ <td>'existing paid'</td>
579
+ <td>radio/tv</td>
580
+ <td>4795</td>
581
+ <td>'&lt;100'</td>
582
+ <td>'&lt;1'</td>
583
+ <td>4</td>
584
+ <td>none</td>
585
+ <td>1</td>
586
+ <td>'no known property'</td>
587
+ <td>30</td>
588
+ <td>none</td>
589
+ <td>own</td>
590
+ <td>1</td>
591
+ <td>'high qualif/self emp/mgmt'</td>
592
+ <td>1</td>
593
+ <td>yes</td>
594
+ <td>yes</td>
595
+ </tr>
596
+ </tbody>
597
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
598
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
599
+ 0 & female & '0<=X<200' & 36 & 'existing paid' & radio/tv & 4795 & '<100' & '<1' & 4 & none & 1 & 'no known property' & 30 & none & own & 1 & 'high qualif/self emp/mgmt' & 1 & yes & yes \\
600
+ \end{tabular}
601
+ ","{'age': 30, 'checking_status': ""'0<=X<200'"", 'credit_amount': 4795, 'credit_history': ""'existing paid'"", 'duration': 36, 'employment': ""'<1'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 4, 'job': ""'high qualif/self emp/mgmt'"", 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'yes', 'property_magnitude': ""'no known property'"", 'purpose': 'radio/tv', 'residence_since': 1, 'savings_status': ""'<100'""}",A 30-year-old female German Foreigner is applying for a loan of 4795 credits for 36 months for radio or tv purposes. She has a checking account with less than 200 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. She has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 1 credits at this bank. She is employed for less than one years and is recognized as a highly qualified employee or is self employed or has managerial position. She has lived in a self-owned house for 1 years. She owns no known property. She owns a telephone and has 1 person that she is liable to provide maintenance for.
602
+ 7,male,'<0',24,'existing paid',furniture/equipment,2359,'100<=X<500',unemployed,1,none,1,'life insurance',33,none,own,1,skilled,1,none,yes,bad,"gender is male, checking_status is '<0', duration is 24, credit_history is 'existing paid', purpose is furniture/equipment, credit_amount is 2359, savings_status is '100<=X<500', employment is unemployed, installment_commitment is 1, other_parties is none, residence_since is 1, property_magnitude is 'life insurance', age is 33, other_payment_plans is none, housing is own, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : male
603
+ - checking_status : '<0'
604
+ - duration : 24
605
+ - credit_history : 'existing paid'
606
+ - purpose : furniture/equipment
607
+ - credit_amount : 2359
608
+ - savings_status : '100<=X<500'
609
+ - employment : unemployed
610
+ - installment_commitment : 1
611
+ - other_parties : none
612
+ - residence_since : 1
613
+ - property_magnitude : 'life insurance'
614
+ - age : 33
615
+ - other_payment_plans : none
616
+ - housing : own
617
+ - existing_credits : 1
618
+ - job : skilled
619
+ - num_dependents : 1
620
+ - own_telephone : none
621
+ - foreign_worker : yes",The gender is male. The checking_status is '<0'. The duration is 24. The credit_history is 'existing paid'. The purpose is furniture/equipment. The credit_amount is 2359. The savings_status is '100<=X<500'. The employment is unemployed. The installment_commitment is 1. The other_parties is none. The residence_since is 1. The property_magnitude is 'life insurance'. The age is 33. The other_payment_plans is none. The housing is own. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
622
+ <thead>
623
+ <tr style=""text-align: right;"">
624
+ <th></th>
625
+ <th>gender</th>
626
+ <th>checking_status</th>
627
+ <th>duration</th>
628
+ <th>credit_history</th>
629
+ <th>purpose</th>
630
+ <th>credit_amount</th>
631
+ <th>savings_status</th>
632
+ <th>employment</th>
633
+ <th>installment_commitment</th>
634
+ <th>other_parties</th>
635
+ <th>residence_since</th>
636
+ <th>property_magnitude</th>
637
+ <th>age</th>
638
+ <th>other_payment_plans</th>
639
+ <th>housing</th>
640
+ <th>existing_credits</th>
641
+ <th>job</th>
642
+ <th>num_dependents</th>
643
+ <th>own_telephone</th>
644
+ <th>foreign_worker</th>
645
+ </tr>
646
+ </thead>
647
+ <tbody>
648
+ <tr>
649
+ <th>0</th>
650
+ <td>male</td>
651
+ <td>'&lt;0'</td>
652
+ <td>24</td>
653
+ <td>'existing paid'</td>
654
+ <td>furniture/equipment</td>
655
+ <td>2359</td>
656
+ <td>'100&lt;=X&lt;500'</td>
657
+ <td>unemployed</td>
658
+ <td>1</td>
659
+ <td>none</td>
660
+ <td>1</td>
661
+ <td>'life insurance'</td>
662
+ <td>33</td>
663
+ <td>none</td>
664
+ <td>own</td>
665
+ <td>1</td>
666
+ <td>skilled</td>
667
+ <td>1</td>
668
+ <td>none</td>
669
+ <td>yes</td>
670
+ </tr>
671
+ </tbody>
672
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
673
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
674
+ 0 & male & '<0' & 24 & 'existing paid' & furniture/equipment & 2359 & '100<=X<500' & unemployed & 1 & none & 1 & 'life insurance' & 33 & none & own & 1 & skilled & 1 & none & yes \\
675
+ \end{tabular}
676
+ ","{'age': 33, 'checking_status': ""'<0'"", 'credit_amount': 2359, 'credit_history': ""'existing paid'"", 'duration': 24, 'employment': 'unemployed', 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'own', 'installment_commitment': 1, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': ""'life insurance'"", 'purpose': 'furniture/equipment', 'residence_since': 1, 'savings_status': ""'100<=X<500'""}",A 33-year-old male German Foreigner is applying for a loan of 2359 credits for 24 months for furniture or equipment purposes. He has a checking account with 0 Deutsche Mark and a savings with more than 100 Deutsche Mark but less than 500 Deutsche Mark. He has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 1%. He has no other installment plans and 1 credits at this bank. He is unemployed. He has lived in a self-owned house for 1 years. He owns life insurance property. He does not own a telephone and has 1 person that he is liable to provide maintenance for.
677
+ 15,female,'no checking',18,'critical/other existing credit',education,1864,'100<=X<500','1<=X<4',4,none,2,'real estate',30,none,own,2,skilled,1,none,yes,bad,"gender is female, checking_status is 'no checking', duration is 18, credit_history is 'critical/other existing credit', purpose is education, credit_amount is 1864, savings_status is '100<=X<500', employment is '1<=X<4', installment_commitment is 4, other_parties is none, residence_since is 2, property_magnitude is 'real estate', age is 30, other_payment_plans is none, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : female
678
+ - checking_status : 'no checking'
679
+ - duration : 18
680
+ - credit_history : 'critical/other existing credit'
681
+ - purpose : education
682
+ - credit_amount : 1864
683
+ - savings_status : '100<=X<500'
684
+ - employment : '1<=X<4'
685
+ - installment_commitment : 4
686
+ - other_parties : none
687
+ - residence_since : 2
688
+ - property_magnitude : 'real estate'
689
+ - age : 30
690
+ - other_payment_plans : none
691
+ - housing : own
692
+ - existing_credits : 2
693
+ - job : skilled
694
+ - num_dependents : 1
695
+ - own_telephone : none
696
+ - foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 18. The credit_history is 'critical/other existing credit'. The purpose is education. The credit_amount is 1864. The savings_status is '100<=X<500'. The employment is '1<=X<4'. The installment_commitment is 4. The other_parties is none. The residence_since is 2. The property_magnitude is 'real estate'. The age is 30. The other_payment_plans is none. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
697
+ <thead>
698
+ <tr style=""text-align: right;"">
699
+ <th></th>
700
+ <th>gender</th>
701
+ <th>checking_status</th>
702
+ <th>duration</th>
703
+ <th>credit_history</th>
704
+ <th>purpose</th>
705
+ <th>credit_amount</th>
706
+ <th>savings_status</th>
707
+ <th>employment</th>
708
+ <th>installment_commitment</th>
709
+ <th>other_parties</th>
710
+ <th>residence_since</th>
711
+ <th>property_magnitude</th>
712
+ <th>age</th>
713
+ <th>other_payment_plans</th>
714
+ <th>housing</th>
715
+ <th>existing_credits</th>
716
+ <th>job</th>
717
+ <th>num_dependents</th>
718
+ <th>own_telephone</th>
719
+ <th>foreign_worker</th>
720
+ </tr>
721
+ </thead>
722
+ <tbody>
723
+ <tr>
724
+ <th>0</th>
725
+ <td>female</td>
726
+ <td>'no checking'</td>
727
+ <td>18</td>
728
+ <td>'critical/other existing credit'</td>
729
+ <td>education</td>
730
+ <td>1864</td>
731
+ <td>'100&lt;=X&lt;500'</td>
732
+ <td>'1&lt;=X&lt;4'</td>
733
+ <td>4</td>
734
+ <td>none</td>
735
+ <td>2</td>
736
+ <td>'real estate'</td>
737
+ <td>30</td>
738
+ <td>none</td>
739
+ <td>own</td>
740
+ <td>2</td>
741
+ <td>skilled</td>
742
+ <td>1</td>
743
+ <td>none</td>
744
+ <td>yes</td>
745
+ </tr>
746
+ </tbody>
747
+ </table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
748
+ & gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
749
+ 0 & female & 'no checking' & 18 & 'critical/other existing credit' & education & 1864 & '100<=X<500' & '1<=X<4' & 4 & none & 2 & 'real estate' & 30 & none & own & 2 & skilled & 1 & none & yes \\
750
+ \end{tabular}
751
+ ","{'age': 30, 'checking_status': ""'no checking'"", 'credit_amount': 1864, 'credit_history': ""'critical/other existing credit'"", 'duration': 18, 'employment': ""'1<=X<4'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 4, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': ""'real estate'"", 'purpose': 'education', 'residence_since': 2, 'savings_status': ""'100<=X<500'""}",A 30-year-old female German Foreigner is applying for a loan of 1864 credits for 18 months for education purposes. She has no checking account and a savings with more than 100 Deutsche Mark but less than 500 Deutsche Mark. She has critical account or has other credits existing but not at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 2 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 2 years. She owns some real estate property. She does not own a telephone and has 1 person that she is liable to provide maintenance for.
new_data/german-test.csv ADDED
The diff for this file is too large to render. See raw diff
 
new_data/german-train.csv ADDED
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new_data/ghana-fewshot-2.csv ADDED
@@ -0,0 +1,121 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Unnamed: 0,sex,amnt req,amnt grnt,ration,maturity,assets val,dec profit,xperience,educatn,age,collateral,locatn,guarantor,relatnshp,purpose,sector,savings,target,great,list,text,html,latex,json,LIFT
2
+ 1,1,1000,1000,0,30.0,3000,600.0,6.0,2,35,3000,0,0,0,1,1,0,Yes,"sex is 1, amnt req is 1000, maturity is 30.0, assets val is 3000, dec profit is 600.0, xperience is 6.0, educatn is 2, age is 35, collateral is 3000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 1, savings is 0","- sex : 1
3
+ - amnt req : 1000
4
+ - maturity : 30.0
5
+ - assets val : 3000
6
+ - dec profit : 600.0
7
+ - xperience : 6.0
8
+ - educatn : 2
9
+ - age : 35
10
+ - collateral : 3000
11
+ - locatn : 0
12
+ - guarantor : 0
13
+ - relatnshp : 0
14
+ - purpose : 1
15
+ - sector : 1
16
+ - savings : 0",The sex is 1. The amnt req is 1000. The maturity is 30.0. The assets val is 3000. The dec profit is 600.0. The xperience is 6.0. The educatn is 2. The age is 35. The collateral is 3000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
17
+ <thead>
18
+ <tr style=""text-align: right;"">
19
+ <th></th>
20
+ <th>sex</th>
21
+ <th>amnt req</th>
22
+ <th>maturity</th>
23
+ <th>assets val</th>
24
+ <th>dec profit</th>
25
+ <th>xperience</th>
26
+ <th>educatn</th>
27
+ <th>age</th>
28
+ <th>collateral</th>
29
+ <th>locatn</th>
30
+ <th>guarantor</th>
31
+ <th>relatnshp</th>
32
+ <th>purpose</th>
33
+ <th>sector</th>
34
+ <th>savings</th>
35
+ </tr>
36
+ </thead>
37
+ <tbody>
38
+ <tr>
39
+ <th>0</th>
40
+ <td>1</td>
41
+ <td>1000</td>
42
+ <td>30.0</td>
43
+ <td>3000</td>
44
+ <td>600.0</td>
45
+ <td>6.0</td>
46
+ <td>2</td>
47
+ <td>35</td>
48
+ <td>3000</td>
49
+ <td>0</td>
50
+ <td>0</td>
51
+ <td>0</td>
52
+ <td>1</td>
53
+ <td>1</td>
54
+ <td>0</td>
55
+ </tr>
56
+ </tbody>
57
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
58
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
59
+ 0 & 1 & 1000 & 30.000000 & 3000 & 600.000000 & 6.000000 & 2 & 35 & 3000 & 0 & 0 & 0 & 1 & 1 & 0 \\
60
+ \end{tabular}
61
+ ","{'age': 35, 'amnt req': 1000, 'assets val': 3000, 'collateral': 3000, 'dec profit': 600.0, 'educatn': 2, 'guarantor': 0, 'locatn': 0, 'maturity': 30.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 1, 'sex': 1, 'xperience': 6.0}",A 35-year-old male is applying for a loan of 1000 cedis. The applicant works in commerce sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 30.0 years. His assets value is 3000 cedis and his declared profits (after tax) is 600.0 cedis. His educational background is secondary and the number of years that he has been in business is 6.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 3000 cedis.
62
+ 0,0,2000,2000,0,36.0,4000,500.0,3.0,1,28,900,0,0,1,0,1,0,Yes,"sex is 0, amnt req is 2000, maturity is 36.0, assets val is 4000, dec profit is 500.0, xperience is 3.0, educatn is 1, age is 28, collateral is 900, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 0, sector is 1, savings is 0","- sex : 0
63
+ - amnt req : 2000
64
+ - maturity : 36.0
65
+ - assets val : 4000
66
+ - dec profit : 500.0
67
+ - xperience : 3.0
68
+ - educatn : 1
69
+ - age : 28
70
+ - collateral : 900
71
+ - locatn : 0
72
+ - guarantor : 0
73
+ - relatnshp : 1
74
+ - purpose : 0
75
+ - sector : 1
76
+ - savings : 0",The sex is 0. The amnt req is 2000. The maturity is 36.0. The assets val is 4000. The dec profit is 500.0. The xperience is 3.0. The educatn is 1. The age is 28. The collateral is 900. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 0. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
77
+ <thead>
78
+ <tr style=""text-align: right;"">
79
+ <th></th>
80
+ <th>sex</th>
81
+ <th>amnt req</th>
82
+ <th>maturity</th>
83
+ <th>assets val</th>
84
+ <th>dec profit</th>
85
+ <th>xperience</th>
86
+ <th>educatn</th>
87
+ <th>age</th>
88
+ <th>collateral</th>
89
+ <th>locatn</th>
90
+ <th>guarantor</th>
91
+ <th>relatnshp</th>
92
+ <th>purpose</th>
93
+ <th>sector</th>
94
+ <th>savings</th>
95
+ </tr>
96
+ </thead>
97
+ <tbody>
98
+ <tr>
99
+ <th>0</th>
100
+ <td>0</td>
101
+ <td>2000</td>
102
+ <td>36.0</td>
103
+ <td>4000</td>
104
+ <td>500.0</td>
105
+ <td>3.0</td>
106
+ <td>1</td>
107
+ <td>28</td>
108
+ <td>900</td>
109
+ <td>0</td>
110
+ <td>0</td>
111
+ <td>1</td>
112
+ <td>0</td>
113
+ <td>1</td>
114
+ <td>0</td>
115
+ </tr>
116
+ </tbody>
117
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
118
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
119
+ 0 & 0 & 2000 & 36.000000 & 4000 & 500.000000 & 3.000000 & 1 & 28 & 900 & 0 & 0 & 1 & 0 & 1 & 0 \\
120
+ \end{tabular}
121
+ ","{'age': 28, 'amnt req': 2000, 'assets val': 4000, 'collateral': 900, 'dec profit': 500.0, 'educatn': 1, 'guarantor': 0, 'locatn': 0, 'maturity': 36.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 1, 'sex': 0, 'xperience': 3.0}",A 28-year-old female is applying for a loan of 2000 cedis. The applicant works in commerce sector and the purpose of the loan is related to her business. The maturity period of the requested loan is 36.0 years. Her assets value is 4000 cedis and her declared profits (after tax) is 500.0 cedis. Her educational background is tertiary and the number of years that she has been in business is 3.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 900 cedis.
new_data/ghana-fewshot-4.csv ADDED
@@ -0,0 +1,241 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Unnamed: 0,sex,amnt req,amnt grnt,ration,maturity,assets val,dec profit,xperience,educatn,age,collateral,locatn,guarantor,relatnshp,purpose,sector,savings,target,great,list,text,html,latex,json,LIFT
2
+ 1,1,1000,1000,0,30.0,3000,600.0,6.0,2,35,3000,0,0,0,1,1,0,Yes,"sex is 1, amnt req is 1000, maturity is 30.0, assets val is 3000, dec profit is 600.0, xperience is 6.0, educatn is 2, age is 35, collateral is 3000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 1, savings is 0","- sex : 1
3
+ - amnt req : 1000
4
+ - maturity : 30.0
5
+ - assets val : 3000
6
+ - dec profit : 600.0
7
+ - xperience : 6.0
8
+ - educatn : 2
9
+ - age : 35
10
+ - collateral : 3000
11
+ - locatn : 0
12
+ - guarantor : 0
13
+ - relatnshp : 0
14
+ - purpose : 1
15
+ - sector : 1
16
+ - savings : 0",The sex is 1. The amnt req is 1000. The maturity is 30.0. The assets val is 3000. The dec profit is 600.0. The xperience is 6.0. The educatn is 2. The age is 35. The collateral is 3000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
17
+ <thead>
18
+ <tr style=""text-align: right;"">
19
+ <th></th>
20
+ <th>sex</th>
21
+ <th>amnt req</th>
22
+ <th>maturity</th>
23
+ <th>assets val</th>
24
+ <th>dec profit</th>
25
+ <th>xperience</th>
26
+ <th>educatn</th>
27
+ <th>age</th>
28
+ <th>collateral</th>
29
+ <th>locatn</th>
30
+ <th>guarantor</th>
31
+ <th>relatnshp</th>
32
+ <th>purpose</th>
33
+ <th>sector</th>
34
+ <th>savings</th>
35
+ </tr>
36
+ </thead>
37
+ <tbody>
38
+ <tr>
39
+ <th>0</th>
40
+ <td>1</td>
41
+ <td>1000</td>
42
+ <td>30.0</td>
43
+ <td>3000</td>
44
+ <td>600.0</td>
45
+ <td>6.0</td>
46
+ <td>2</td>
47
+ <td>35</td>
48
+ <td>3000</td>
49
+ <td>0</td>
50
+ <td>0</td>
51
+ <td>0</td>
52
+ <td>1</td>
53
+ <td>1</td>
54
+ <td>0</td>
55
+ </tr>
56
+ </tbody>
57
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
58
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
59
+ 0 & 1 & 1000 & 30.000000 & 3000 & 600.000000 & 6.000000 & 2 & 35 & 3000 & 0 & 0 & 0 & 1 & 1 & 0 \\
60
+ \end{tabular}
61
+ ","{'age': 35, 'amnt req': 1000, 'assets val': 3000, 'collateral': 3000, 'dec profit': 600.0, 'educatn': 2, 'guarantor': 0, 'locatn': 0, 'maturity': 30.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 1, 'sex': 1, 'xperience': 6.0}",A 35-year-old male is applying for a loan of 1000 cedis. The applicant works in commerce sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 30.0 years. His assets value is 3000 cedis and his declared profits (after tax) is 600.0 cedis. His educational background is secondary and the number of years that he has been in business is 6.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 3000 cedis.
62
+ 0,0,2000,2000,0,36.0,4000,500.0,3.0,1,28,900,0,0,1,0,1,0,Yes,"sex is 0, amnt req is 2000, maturity is 36.0, assets val is 4000, dec profit is 500.0, xperience is 3.0, educatn is 1, age is 28, collateral is 900, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 0, sector is 1, savings is 0","- sex : 0
63
+ - amnt req : 2000
64
+ - maturity : 36.0
65
+ - assets val : 4000
66
+ - dec profit : 500.0
67
+ - xperience : 3.0
68
+ - educatn : 1
69
+ - age : 28
70
+ - collateral : 900
71
+ - locatn : 0
72
+ - guarantor : 0
73
+ - relatnshp : 1
74
+ - purpose : 0
75
+ - sector : 1
76
+ - savings : 0",The sex is 0. The amnt req is 2000. The maturity is 36.0. The assets val is 4000. The dec profit is 500.0. The xperience is 3.0. The educatn is 1. The age is 28. The collateral is 900. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 0. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
77
+ <thead>
78
+ <tr style=""text-align: right;"">
79
+ <th></th>
80
+ <th>sex</th>
81
+ <th>amnt req</th>
82
+ <th>maturity</th>
83
+ <th>assets val</th>
84
+ <th>dec profit</th>
85
+ <th>xperience</th>
86
+ <th>educatn</th>
87
+ <th>age</th>
88
+ <th>collateral</th>
89
+ <th>locatn</th>
90
+ <th>guarantor</th>
91
+ <th>relatnshp</th>
92
+ <th>purpose</th>
93
+ <th>sector</th>
94
+ <th>savings</th>
95
+ </tr>
96
+ </thead>
97
+ <tbody>
98
+ <tr>
99
+ <th>0</th>
100
+ <td>0</td>
101
+ <td>2000</td>
102
+ <td>36.0</td>
103
+ <td>4000</td>
104
+ <td>500.0</td>
105
+ <td>3.0</td>
106
+ <td>1</td>
107
+ <td>28</td>
108
+ <td>900</td>
109
+ <td>0</td>
110
+ <td>0</td>
111
+ <td>1</td>
112
+ <td>0</td>
113
+ <td>1</td>
114
+ <td>0</td>
115
+ </tr>
116
+ </tbody>
117
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
118
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
119
+ 0 & 0 & 2000 & 36.000000 & 4000 & 500.000000 & 3.000000 & 1 & 28 & 900 & 0 & 0 & 1 & 0 & 1 & 0 \\
120
+ \end{tabular}
121
+ ","{'age': 28, 'amnt req': 2000, 'assets val': 4000, 'collateral': 900, 'dec profit': 500.0, 'educatn': 1, 'guarantor': 0, 'locatn': 0, 'maturity': 36.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 1, 'sex': 0, 'xperience': 3.0}",A 28-year-old female is applying for a loan of 2000 cedis. The applicant works in commerce sector and the purpose of the loan is related to her business. The maturity period of the requested loan is 36.0 years. Her assets value is 4000 cedis and her declared profits (after tax) is 500.0 cedis. Her educational background is tertiary and the number of years that she has been in business is 3.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 900 cedis.
122
+ 4,1,2000,2000,0,60.0,2800,320.0,12.0,3,42,2000,0,0,0,1,5,0,Yes,"sex is 1, amnt req is 2000, maturity is 60.0, assets val is 2800, dec profit is 320.0, xperience is 12.0, educatn is 3, age is 42, collateral is 2000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 5, savings is 0","- sex : 1
123
+ - amnt req : 2000
124
+ - maturity : 60.0
125
+ - assets val : 2800
126
+ - dec profit : 320.0
127
+ - xperience : 12.0
128
+ - educatn : 3
129
+ - age : 42
130
+ - collateral : 2000
131
+ - locatn : 0
132
+ - guarantor : 0
133
+ - relatnshp : 0
134
+ - purpose : 1
135
+ - sector : 5
136
+ - savings : 0",The sex is 1. The amnt req is 2000. The maturity is 60.0. The assets val is 2800. The dec profit is 320.0. The xperience is 12.0. The educatn is 3. The age is 42. The collateral is 2000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 5. The savings is 0,"<table border=""1"" class=""dataframe"">
137
+ <thead>
138
+ <tr style=""text-align: right;"">
139
+ <th></th>
140
+ <th>sex</th>
141
+ <th>amnt req</th>
142
+ <th>maturity</th>
143
+ <th>assets val</th>
144
+ <th>dec profit</th>
145
+ <th>xperience</th>
146
+ <th>educatn</th>
147
+ <th>age</th>
148
+ <th>collateral</th>
149
+ <th>locatn</th>
150
+ <th>guarantor</th>
151
+ <th>relatnshp</th>
152
+ <th>purpose</th>
153
+ <th>sector</th>
154
+ <th>savings</th>
155
+ </tr>
156
+ </thead>
157
+ <tbody>
158
+ <tr>
159
+ <th>0</th>
160
+ <td>1</td>
161
+ <td>2000</td>
162
+ <td>60.0</td>
163
+ <td>2800</td>
164
+ <td>320.0</td>
165
+ <td>12.0</td>
166
+ <td>3</td>
167
+ <td>42</td>
168
+ <td>2000</td>
169
+ <td>0</td>
170
+ <td>0</td>
171
+ <td>0</td>
172
+ <td>1</td>
173
+ <td>5</td>
174
+ <td>0</td>
175
+ </tr>
176
+ </tbody>
177
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
178
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
179
+ 0 & 1 & 2000 & 60.000000 & 2800 & 320.000000 & 12.000000 & 3 & 42 & 2000 & 0 & 0 & 0 & 1 & 5 & 0 \\
180
+ \end{tabular}
181
+ ","{'age': 42, 'amnt req': 2000, 'assets val': 2800, 'collateral': 2000, 'dec profit': 320.0, 'educatn': 3, 'guarantor': 0, 'locatn': 0, 'maturity': 60.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 5, 'sex': 1, 'xperience': 12.0}",A 42-year-old male is applying for a loan of 2000 cedis. The applicant works in service sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 60.0 years. His assets value is 2800 cedis and his declared profits (after tax) is 320.0 cedis. His educational background is primary and the number of years that he has been in business is 12.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 2000 cedis.
182
+ 2,0,5000,3000,1,40.0,7000,1350.0,5.0,3,35,2000,0,0,1,1,4,0,No,"sex is 0, amnt req is 5000, maturity is 40.0, assets val is 7000, dec profit is 1350.0, xperience is 5.0, educatn is 3, age is 35, collateral is 2000, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 1, sector is 4, savings is 0","- sex : 0
183
+ - amnt req : 5000
184
+ - maturity : 40.0
185
+ - assets val : 7000
186
+ - dec profit : 1350.0
187
+ - xperience : 5.0
188
+ - educatn : 3
189
+ - age : 35
190
+ - collateral : 2000
191
+ - locatn : 0
192
+ - guarantor : 0
193
+ - relatnshp : 1
194
+ - purpose : 1
195
+ - sector : 4
196
+ - savings : 0",The sex is 0. The amnt req is 5000. The maturity is 40.0. The assets val is 7000. The dec profit is 1350.0. The xperience is 5.0. The educatn is 3. The age is 35. The collateral is 2000. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 1. The sector is 4. The savings is 0,"<table border=""1"" class=""dataframe"">
197
+ <thead>
198
+ <tr style=""text-align: right;"">
199
+ <th></th>
200
+ <th>sex</th>
201
+ <th>amnt req</th>
202
+ <th>maturity</th>
203
+ <th>assets val</th>
204
+ <th>dec profit</th>
205
+ <th>xperience</th>
206
+ <th>educatn</th>
207
+ <th>age</th>
208
+ <th>collateral</th>
209
+ <th>locatn</th>
210
+ <th>guarantor</th>
211
+ <th>relatnshp</th>
212
+ <th>purpose</th>
213
+ <th>sector</th>
214
+ <th>savings</th>
215
+ </tr>
216
+ </thead>
217
+ <tbody>
218
+ <tr>
219
+ <th>0</th>
220
+ <td>0</td>
221
+ <td>5000</td>
222
+ <td>40.0</td>
223
+ <td>7000</td>
224
+ <td>1350.0</td>
225
+ <td>5.0</td>
226
+ <td>3</td>
227
+ <td>35</td>
228
+ <td>2000</td>
229
+ <td>0</td>
230
+ <td>0</td>
231
+ <td>1</td>
232
+ <td>1</td>
233
+ <td>4</td>
234
+ <td>0</td>
235
+ </tr>
236
+ </tbody>
237
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
238
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
239
+ 0 & 0 & 5000 & 40.000000 & 7000 & 1350.000000 & 5.000000 & 3 & 35 & 2000 & 0 & 0 & 1 & 1 & 4 & 0 \\
240
+ \end{tabular}
241
+ ","{'age': 35, 'amnt req': 5000, 'assets val': 7000, 'collateral': 2000, 'dec profit': 1350.0, 'educatn': 3, 'guarantor': 0, 'locatn': 0, 'maturity': 40.0, 'purpose': 1, 'relatnshp': 1, 'savings': 0, 'sector': 4, 'sex': 0, 'xperience': 5.0}",A 35-year-old female is applying for a loan of 5000 cedis. The applicant works in agriculture sector and the purpose of the loan is not related to her business. The maturity period of the requested loan is 40.0 years. Her assets value is 7000 cedis and her declared profits (after tax) is 1350.0 cedis. Her educational background is primary and the number of years that she has been in business is 5.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 2000 cedis.
new_data/ghana-fewshot-6.csv ADDED
@@ -0,0 +1,361 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Unnamed: 0,sex,amnt req,amnt grnt,ration,maturity,assets val,dec profit,xperience,educatn,age,collateral,locatn,guarantor,relatnshp,purpose,sector,savings,target,great,list,text,html,latex,json,LIFT
2
+ 1,1,1000,1000,0,30.0,3000,600.0,6.0,2,35,3000,0,0,0,1,1,0,Yes,"sex is 1, amnt req is 1000, maturity is 30.0, assets val is 3000, dec profit is 600.0, xperience is 6.0, educatn is 2, age is 35, collateral is 3000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 1, savings is 0","- sex : 1
3
+ - amnt req : 1000
4
+ - maturity : 30.0
5
+ - assets val : 3000
6
+ - dec profit : 600.0
7
+ - xperience : 6.0
8
+ - educatn : 2
9
+ - age : 35
10
+ - collateral : 3000
11
+ - locatn : 0
12
+ - guarantor : 0
13
+ - relatnshp : 0
14
+ - purpose : 1
15
+ - sector : 1
16
+ - savings : 0",The sex is 1. The amnt req is 1000. The maturity is 30.0. The assets val is 3000. The dec profit is 600.0. The xperience is 6.0. The educatn is 2. The age is 35. The collateral is 3000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
17
+ <thead>
18
+ <tr style=""text-align: right;"">
19
+ <th></th>
20
+ <th>sex</th>
21
+ <th>amnt req</th>
22
+ <th>maturity</th>
23
+ <th>assets val</th>
24
+ <th>dec profit</th>
25
+ <th>xperience</th>
26
+ <th>educatn</th>
27
+ <th>age</th>
28
+ <th>collateral</th>
29
+ <th>locatn</th>
30
+ <th>guarantor</th>
31
+ <th>relatnshp</th>
32
+ <th>purpose</th>
33
+ <th>sector</th>
34
+ <th>savings</th>
35
+ </tr>
36
+ </thead>
37
+ <tbody>
38
+ <tr>
39
+ <th>0</th>
40
+ <td>1</td>
41
+ <td>1000</td>
42
+ <td>30.0</td>
43
+ <td>3000</td>
44
+ <td>600.0</td>
45
+ <td>6.0</td>
46
+ <td>2</td>
47
+ <td>35</td>
48
+ <td>3000</td>
49
+ <td>0</td>
50
+ <td>0</td>
51
+ <td>0</td>
52
+ <td>1</td>
53
+ <td>1</td>
54
+ <td>0</td>
55
+ </tr>
56
+ </tbody>
57
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
58
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
59
+ 0 & 1 & 1000 & 30.000000 & 3000 & 600.000000 & 6.000000 & 2 & 35 & 3000 & 0 & 0 & 0 & 1 & 1 & 0 \\
60
+ \end{tabular}
61
+ ","{'age': 35, 'amnt req': 1000, 'assets val': 3000, 'collateral': 3000, 'dec profit': 600.0, 'educatn': 2, 'guarantor': 0, 'locatn': 0, 'maturity': 30.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 1, 'sex': 1, 'xperience': 6.0}",A 35-year-old male is applying for a loan of 1000 cedis. The applicant works in commerce sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 30.0 years. His assets value is 3000 cedis and his declared profits (after tax) is 600.0 cedis. His educational background is secondary and the number of years that he has been in business is 6.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 3000 cedis.
62
+ 0,0,2000,2000,0,36.0,4000,500.0,3.0,1,28,900,0,0,1,0,1,0,Yes,"sex is 0, amnt req is 2000, maturity is 36.0, assets val is 4000, dec profit is 500.0, xperience is 3.0, educatn is 1, age is 28, collateral is 900, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 0, sector is 1, savings is 0","- sex : 0
63
+ - amnt req : 2000
64
+ - maturity : 36.0
65
+ - assets val : 4000
66
+ - dec profit : 500.0
67
+ - xperience : 3.0
68
+ - educatn : 1
69
+ - age : 28
70
+ - collateral : 900
71
+ - locatn : 0
72
+ - guarantor : 0
73
+ - relatnshp : 1
74
+ - purpose : 0
75
+ - sector : 1
76
+ - savings : 0",The sex is 0. The amnt req is 2000. The maturity is 36.0. The assets val is 4000. The dec profit is 500.0. The xperience is 3.0. The educatn is 1. The age is 28. The collateral is 900. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 0. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
77
+ <thead>
78
+ <tr style=""text-align: right;"">
79
+ <th></th>
80
+ <th>sex</th>
81
+ <th>amnt req</th>
82
+ <th>maturity</th>
83
+ <th>assets val</th>
84
+ <th>dec profit</th>
85
+ <th>xperience</th>
86
+ <th>educatn</th>
87
+ <th>age</th>
88
+ <th>collateral</th>
89
+ <th>locatn</th>
90
+ <th>guarantor</th>
91
+ <th>relatnshp</th>
92
+ <th>purpose</th>
93
+ <th>sector</th>
94
+ <th>savings</th>
95
+ </tr>
96
+ </thead>
97
+ <tbody>
98
+ <tr>
99
+ <th>0</th>
100
+ <td>0</td>
101
+ <td>2000</td>
102
+ <td>36.0</td>
103
+ <td>4000</td>
104
+ <td>500.0</td>
105
+ <td>3.0</td>
106
+ <td>1</td>
107
+ <td>28</td>
108
+ <td>900</td>
109
+ <td>0</td>
110
+ <td>0</td>
111
+ <td>1</td>
112
+ <td>0</td>
113
+ <td>1</td>
114
+ <td>0</td>
115
+ </tr>
116
+ </tbody>
117
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
118
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
119
+ 0 & 0 & 2000 & 36.000000 & 4000 & 500.000000 & 3.000000 & 1 & 28 & 900 & 0 & 0 & 1 & 0 & 1 & 0 \\
120
+ \end{tabular}
121
+ ","{'age': 28, 'amnt req': 2000, 'assets val': 4000, 'collateral': 900, 'dec profit': 500.0, 'educatn': 1, 'guarantor': 0, 'locatn': 0, 'maturity': 36.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 1, 'sex': 0, 'xperience': 3.0}",A 28-year-old female is applying for a loan of 2000 cedis. The applicant works in commerce sector and the purpose of the loan is related to her business. The maturity period of the requested loan is 36.0 years. Her assets value is 4000 cedis and her declared profits (after tax) is 500.0 cedis. Her educational background is tertiary and the number of years that she has been in business is 3.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 900 cedis.
122
+ 4,1,2000,2000,0,60.0,2800,320.0,12.0,3,42,2000,0,0,0,1,5,0,Yes,"sex is 1, amnt req is 2000, maturity is 60.0, assets val is 2800, dec profit is 320.0, xperience is 12.0, educatn is 3, age is 42, collateral is 2000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 5, savings is 0","- sex : 1
123
+ - amnt req : 2000
124
+ - maturity : 60.0
125
+ - assets val : 2800
126
+ - dec profit : 320.0
127
+ - xperience : 12.0
128
+ - educatn : 3
129
+ - age : 42
130
+ - collateral : 2000
131
+ - locatn : 0
132
+ - guarantor : 0
133
+ - relatnshp : 0
134
+ - purpose : 1
135
+ - sector : 5
136
+ - savings : 0",The sex is 1. The amnt req is 2000. The maturity is 60.0. The assets val is 2800. The dec profit is 320.0. The xperience is 12.0. The educatn is 3. The age is 42. The collateral is 2000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 5. The savings is 0,"<table border=""1"" class=""dataframe"">
137
+ <thead>
138
+ <tr style=""text-align: right;"">
139
+ <th></th>
140
+ <th>sex</th>
141
+ <th>amnt req</th>
142
+ <th>maturity</th>
143
+ <th>assets val</th>
144
+ <th>dec profit</th>
145
+ <th>xperience</th>
146
+ <th>educatn</th>
147
+ <th>age</th>
148
+ <th>collateral</th>
149
+ <th>locatn</th>
150
+ <th>guarantor</th>
151
+ <th>relatnshp</th>
152
+ <th>purpose</th>
153
+ <th>sector</th>
154
+ <th>savings</th>
155
+ </tr>
156
+ </thead>
157
+ <tbody>
158
+ <tr>
159
+ <th>0</th>
160
+ <td>1</td>
161
+ <td>2000</td>
162
+ <td>60.0</td>
163
+ <td>2800</td>
164
+ <td>320.0</td>
165
+ <td>12.0</td>
166
+ <td>3</td>
167
+ <td>42</td>
168
+ <td>2000</td>
169
+ <td>0</td>
170
+ <td>0</td>
171
+ <td>0</td>
172
+ <td>1</td>
173
+ <td>5</td>
174
+ <td>0</td>
175
+ </tr>
176
+ </tbody>
177
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
178
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
179
+ 0 & 1 & 2000 & 60.000000 & 2800 & 320.000000 & 12.000000 & 3 & 42 & 2000 & 0 & 0 & 0 & 1 & 5 & 0 \\
180
+ \end{tabular}
181
+ ","{'age': 42, 'amnt req': 2000, 'assets val': 2800, 'collateral': 2000, 'dec profit': 320.0, 'educatn': 3, 'guarantor': 0, 'locatn': 0, 'maturity': 60.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 5, 'sex': 1, 'xperience': 12.0}",A 42-year-old male is applying for a loan of 2000 cedis. The applicant works in service sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 60.0 years. His assets value is 2800 cedis and his declared profits (after tax) is 320.0 cedis. His educational background is primary and the number of years that he has been in business is 12.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 2000 cedis.
182
+ 2,0,5000,3000,1,40.0,7000,1350.0,5.0,3,35,2000,0,0,1,1,4,0,No,"sex is 0, amnt req is 5000, maturity is 40.0, assets val is 7000, dec profit is 1350.0, xperience is 5.0, educatn is 3, age is 35, collateral is 2000, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 1, sector is 4, savings is 0","- sex : 0
183
+ - amnt req : 5000
184
+ - maturity : 40.0
185
+ - assets val : 7000
186
+ - dec profit : 1350.0
187
+ - xperience : 5.0
188
+ - educatn : 3
189
+ - age : 35
190
+ - collateral : 2000
191
+ - locatn : 0
192
+ - guarantor : 0
193
+ - relatnshp : 1
194
+ - purpose : 1
195
+ - sector : 4
196
+ - savings : 0",The sex is 0. The amnt req is 5000. The maturity is 40.0. The assets val is 7000. The dec profit is 1350.0. The xperience is 5.0. The educatn is 3. The age is 35. The collateral is 2000. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 1. The sector is 4. The savings is 0,"<table border=""1"" class=""dataframe"">
197
+ <thead>
198
+ <tr style=""text-align: right;"">
199
+ <th></th>
200
+ <th>sex</th>
201
+ <th>amnt req</th>
202
+ <th>maturity</th>
203
+ <th>assets val</th>
204
+ <th>dec profit</th>
205
+ <th>xperience</th>
206
+ <th>educatn</th>
207
+ <th>age</th>
208
+ <th>collateral</th>
209
+ <th>locatn</th>
210
+ <th>guarantor</th>
211
+ <th>relatnshp</th>
212
+ <th>purpose</th>
213
+ <th>sector</th>
214
+ <th>savings</th>
215
+ </tr>
216
+ </thead>
217
+ <tbody>
218
+ <tr>
219
+ <th>0</th>
220
+ <td>0</td>
221
+ <td>5000</td>
222
+ <td>40.0</td>
223
+ <td>7000</td>
224
+ <td>1350.0</td>
225
+ <td>5.0</td>
226
+ <td>3</td>
227
+ <td>35</td>
228
+ <td>2000</td>
229
+ <td>0</td>
230
+ <td>0</td>
231
+ <td>1</td>
232
+ <td>1</td>
233
+ <td>4</td>
234
+ <td>0</td>
235
+ </tr>
236
+ </tbody>
237
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
238
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
239
+ 0 & 0 & 5000 & 40.000000 & 7000 & 1350.000000 & 5.000000 & 3 & 35 & 2000 & 0 & 0 & 1 & 1 & 4 & 0 \\
240
+ \end{tabular}
241
+ ","{'age': 35, 'amnt req': 5000, 'assets val': 7000, 'collateral': 2000, 'dec profit': 1350.0, 'educatn': 3, 'guarantor': 0, 'locatn': 0, 'maturity': 40.0, 'purpose': 1, 'relatnshp': 1, 'savings': 0, 'sector': 4, 'sex': 0, 'xperience': 5.0}",A 35-year-old female is applying for a loan of 5000 cedis. The applicant works in agriculture sector and the purpose of the loan is not related to her business. The maturity period of the requested loan is 40.0 years. Her assets value is 7000 cedis and her declared profits (after tax) is 1350.0 cedis. Her educational background is primary and the number of years that she has been in business is 5.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 2000 cedis.
242
+ 6,1,1000,500,1,60.0,1000,120.0,8.0,3,56,1000,1,0,0,0,5,0,No,"sex is 1, amnt req is 1000, maturity is 60.0, assets val is 1000, dec profit is 120.0, xperience is 8.0, educatn is 3, age is 56, collateral is 1000, locatn is 1, guarantor is 0, relatnshp is 0, purpose is 0, sector is 5, savings is 0","- sex : 1
243
+ - amnt req : 1000
244
+ - maturity : 60.0
245
+ - assets val : 1000
246
+ - dec profit : 120.0
247
+ - xperience : 8.0
248
+ - educatn : 3
249
+ - age : 56
250
+ - collateral : 1000
251
+ - locatn : 1
252
+ - guarantor : 0
253
+ - relatnshp : 0
254
+ - purpose : 0
255
+ - sector : 5
256
+ - savings : 0",The sex is 1. The amnt req is 1000. The maturity is 60.0. The assets val is 1000. The dec profit is 120.0. The xperience is 8.0. The educatn is 3. The age is 56. The collateral is 1000. The locatn is 1. The guarantor is 0. The relatnshp is 0. The purpose is 0. The sector is 5. The savings is 0,"<table border=""1"" class=""dataframe"">
257
+ <thead>
258
+ <tr style=""text-align: right;"">
259
+ <th></th>
260
+ <th>sex</th>
261
+ <th>amnt req</th>
262
+ <th>maturity</th>
263
+ <th>assets val</th>
264
+ <th>dec profit</th>
265
+ <th>xperience</th>
266
+ <th>educatn</th>
267
+ <th>age</th>
268
+ <th>collateral</th>
269
+ <th>locatn</th>
270
+ <th>guarantor</th>
271
+ <th>relatnshp</th>
272
+ <th>purpose</th>
273
+ <th>sector</th>
274
+ <th>savings</th>
275
+ </tr>
276
+ </thead>
277
+ <tbody>
278
+ <tr>
279
+ <th>0</th>
280
+ <td>1</td>
281
+ <td>1000</td>
282
+ <td>60.0</td>
283
+ <td>1000</td>
284
+ <td>120.0</td>
285
+ <td>8.0</td>
286
+ <td>3</td>
287
+ <td>56</td>
288
+ <td>1000</td>
289
+ <td>1</td>
290
+ <td>0</td>
291
+ <td>0</td>
292
+ <td>0</td>
293
+ <td>5</td>
294
+ <td>0</td>
295
+ </tr>
296
+ </tbody>
297
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
298
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
299
+ 0 & 1 & 1000 & 60.000000 & 1000 & 120.000000 & 8.000000 & 3 & 56 & 1000 & 1 & 0 & 0 & 0 & 5 & 0 \\
300
+ \end{tabular}
301
+ ","{'age': 56, 'amnt req': 1000, 'assets val': 1000, 'collateral': 1000, 'dec profit': 120.0, 'educatn': 3, 'guarantor': 0, 'locatn': 1, 'maturity': 60.0, 'purpose': 0, 'relatnshp': 0, 'savings': 0, 'sector': 5, 'sex': 1, 'xperience': 8.0}",A 56-year-old male is applying for a loan of 1000 cedis. The applicant works in service sector and the purpose of the loan is related to his business. The maturity period of the requested loan is 60.0 years. His assets value is 1000 cedis and his declared profits (after tax) is 120.0 cedis. His educational background is primary and the number of years that he has been in business is 8.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He resides or have his business close to the bank. The value of his collateral is 1000 cedis.
302
+ 3,0,1000,1000,0,24.0,2500,590.0,6.0,1,25,20000,1,0,1,0,1,0,Yes,"sex is 0, amnt req is 1000, maturity is 24.0, assets val is 2500, dec profit is 590.0, xperience is 6.0, educatn is 1, age is 25, collateral is 20000, locatn is 1, guarantor is 0, relatnshp is 1, purpose is 0, sector is 1, savings is 0","- sex : 0
303
+ - amnt req : 1000
304
+ - maturity : 24.0
305
+ - assets val : 2500
306
+ - dec profit : 590.0
307
+ - xperience : 6.0
308
+ - educatn : 1
309
+ - age : 25
310
+ - collateral : 20000
311
+ - locatn : 1
312
+ - guarantor : 0
313
+ - relatnshp : 1
314
+ - purpose : 0
315
+ - sector : 1
316
+ - savings : 0",The sex is 0. The amnt req is 1000. The maturity is 24.0. The assets val is 2500. The dec profit is 590.0. The xperience is 6.0. The educatn is 1. The age is 25. The collateral is 20000. The locatn is 1. The guarantor is 0. The relatnshp is 1. The purpose is 0. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
317
+ <thead>
318
+ <tr style=""text-align: right;"">
319
+ <th></th>
320
+ <th>sex</th>
321
+ <th>amnt req</th>
322
+ <th>maturity</th>
323
+ <th>assets val</th>
324
+ <th>dec profit</th>
325
+ <th>xperience</th>
326
+ <th>educatn</th>
327
+ <th>age</th>
328
+ <th>collateral</th>
329
+ <th>locatn</th>
330
+ <th>guarantor</th>
331
+ <th>relatnshp</th>
332
+ <th>purpose</th>
333
+ <th>sector</th>
334
+ <th>savings</th>
335
+ </tr>
336
+ </thead>
337
+ <tbody>
338
+ <tr>
339
+ <th>0</th>
340
+ <td>0</td>
341
+ <td>1000</td>
342
+ <td>24.0</td>
343
+ <td>2500</td>
344
+ <td>590.0</td>
345
+ <td>6.0</td>
346
+ <td>1</td>
347
+ <td>25</td>
348
+ <td>20000</td>
349
+ <td>1</td>
350
+ <td>0</td>
351
+ <td>1</td>
352
+ <td>0</td>
353
+ <td>1</td>
354
+ <td>0</td>
355
+ </tr>
356
+ </tbody>
357
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
358
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
359
+ 0 & 0 & 1000 & 24.000000 & 2500 & 590.000000 & 6.000000 & 1 & 25 & 20000 & 1 & 0 & 1 & 0 & 1 & 0 \\
360
+ \end{tabular}
361
+ ","{'age': 25, 'amnt req': 1000, 'assets val': 2500, 'collateral': 20000, 'dec profit': 590.0, 'educatn': 1, 'guarantor': 0, 'locatn': 1, 'maturity': 24.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 1, 'sex': 0, 'xperience': 6.0}",A 25-year-old female is applying for a loan of 1000 cedis. The applicant works in commerce sector and the purpose of the loan is related to her business. The maturity period of the requested loan is 24.0 years. Her assets value is 2500 cedis and her declared profits (after tax) is 590.0 cedis. Her educational background is tertiary and the number of years that she has been in business is 6.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She resides or have her business close to the bank. The value of her collateral is 20000 cedis.
new_data/ghana-fewshot-8.csv ADDED
@@ -0,0 +1,481 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Unnamed: 0,sex,amnt req,amnt grnt,ration,maturity,assets val,dec profit,xperience,educatn,age,collateral,locatn,guarantor,relatnshp,purpose,sector,savings,target,great,list,text,html,latex,json,LIFT
2
+ 1,1,1000,1000,0,30.0,3000,600.0,6.0,2,35,3000,0,0,0,1,1,0,Yes,"sex is 1, amnt req is 1000, maturity is 30.0, assets val is 3000, dec profit is 600.0, xperience is 6.0, educatn is 2, age is 35, collateral is 3000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 1, savings is 0","- sex : 1
3
+ - amnt req : 1000
4
+ - maturity : 30.0
5
+ - assets val : 3000
6
+ - dec profit : 600.0
7
+ - xperience : 6.0
8
+ - educatn : 2
9
+ - age : 35
10
+ - collateral : 3000
11
+ - locatn : 0
12
+ - guarantor : 0
13
+ - relatnshp : 0
14
+ - purpose : 1
15
+ - sector : 1
16
+ - savings : 0",The sex is 1. The amnt req is 1000. The maturity is 30.0. The assets val is 3000. The dec profit is 600.0. The xperience is 6.0. The educatn is 2. The age is 35. The collateral is 3000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
17
+ <thead>
18
+ <tr style=""text-align: right;"">
19
+ <th></th>
20
+ <th>sex</th>
21
+ <th>amnt req</th>
22
+ <th>maturity</th>
23
+ <th>assets val</th>
24
+ <th>dec profit</th>
25
+ <th>xperience</th>
26
+ <th>educatn</th>
27
+ <th>age</th>
28
+ <th>collateral</th>
29
+ <th>locatn</th>
30
+ <th>guarantor</th>
31
+ <th>relatnshp</th>
32
+ <th>purpose</th>
33
+ <th>sector</th>
34
+ <th>savings</th>
35
+ </tr>
36
+ </thead>
37
+ <tbody>
38
+ <tr>
39
+ <th>0</th>
40
+ <td>1</td>
41
+ <td>1000</td>
42
+ <td>30.0</td>
43
+ <td>3000</td>
44
+ <td>600.0</td>
45
+ <td>6.0</td>
46
+ <td>2</td>
47
+ <td>35</td>
48
+ <td>3000</td>
49
+ <td>0</td>
50
+ <td>0</td>
51
+ <td>0</td>
52
+ <td>1</td>
53
+ <td>1</td>
54
+ <td>0</td>
55
+ </tr>
56
+ </tbody>
57
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
58
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
59
+ 0 & 1 & 1000 & 30.000000 & 3000 & 600.000000 & 6.000000 & 2 & 35 & 3000 & 0 & 0 & 0 & 1 & 1 & 0 \\
60
+ \end{tabular}
61
+ ","{'age': 35, 'amnt req': 1000, 'assets val': 3000, 'collateral': 3000, 'dec profit': 600.0, 'educatn': 2, 'guarantor': 0, 'locatn': 0, 'maturity': 30.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 1, 'sex': 1, 'xperience': 6.0}",A 35-year-old male is applying for a loan of 1000 cedis. The applicant works in commerce sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 30.0 years. His assets value is 3000 cedis and his declared profits (after tax) is 600.0 cedis. His educational background is secondary and the number of years that he has been in business is 6.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 3000 cedis.
62
+ 0,0,2000,2000,0,36.0,4000,500.0,3.0,1,28,900,0,0,1,0,1,0,Yes,"sex is 0, amnt req is 2000, maturity is 36.0, assets val is 4000, dec profit is 500.0, xperience is 3.0, educatn is 1, age is 28, collateral is 900, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 0, sector is 1, savings is 0","- sex : 0
63
+ - amnt req : 2000
64
+ - maturity : 36.0
65
+ - assets val : 4000
66
+ - dec profit : 500.0
67
+ - xperience : 3.0
68
+ - educatn : 1
69
+ - age : 28
70
+ - collateral : 900
71
+ - locatn : 0
72
+ - guarantor : 0
73
+ - relatnshp : 1
74
+ - purpose : 0
75
+ - sector : 1
76
+ - savings : 0",The sex is 0. The amnt req is 2000. The maturity is 36.0. The assets val is 4000. The dec profit is 500.0. The xperience is 3.0. The educatn is 1. The age is 28. The collateral is 900. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 0. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
77
+ <thead>
78
+ <tr style=""text-align: right;"">
79
+ <th></th>
80
+ <th>sex</th>
81
+ <th>amnt req</th>
82
+ <th>maturity</th>
83
+ <th>assets val</th>
84
+ <th>dec profit</th>
85
+ <th>xperience</th>
86
+ <th>educatn</th>
87
+ <th>age</th>
88
+ <th>collateral</th>
89
+ <th>locatn</th>
90
+ <th>guarantor</th>
91
+ <th>relatnshp</th>
92
+ <th>purpose</th>
93
+ <th>sector</th>
94
+ <th>savings</th>
95
+ </tr>
96
+ </thead>
97
+ <tbody>
98
+ <tr>
99
+ <th>0</th>
100
+ <td>0</td>
101
+ <td>2000</td>
102
+ <td>36.0</td>
103
+ <td>4000</td>
104
+ <td>500.0</td>
105
+ <td>3.0</td>
106
+ <td>1</td>
107
+ <td>28</td>
108
+ <td>900</td>
109
+ <td>0</td>
110
+ <td>0</td>
111
+ <td>1</td>
112
+ <td>0</td>
113
+ <td>1</td>
114
+ <td>0</td>
115
+ </tr>
116
+ </tbody>
117
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
118
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
119
+ 0 & 0 & 2000 & 36.000000 & 4000 & 500.000000 & 3.000000 & 1 & 28 & 900 & 0 & 0 & 1 & 0 & 1 & 0 \\
120
+ \end{tabular}
121
+ ","{'age': 28, 'amnt req': 2000, 'assets val': 4000, 'collateral': 900, 'dec profit': 500.0, 'educatn': 1, 'guarantor': 0, 'locatn': 0, 'maturity': 36.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 1, 'sex': 0, 'xperience': 3.0}",A 28-year-old female is applying for a loan of 2000 cedis. The applicant works in commerce sector and the purpose of the loan is related to her business. The maturity period of the requested loan is 36.0 years. Her assets value is 4000 cedis and her declared profits (after tax) is 500.0 cedis. Her educational background is tertiary and the number of years that she has been in business is 3.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 900 cedis.
122
+ 4,1,2000,2000,0,60.0,2800,320.0,12.0,3,42,2000,0,0,0,1,5,0,Yes,"sex is 1, amnt req is 2000, maturity is 60.0, assets val is 2800, dec profit is 320.0, xperience is 12.0, educatn is 3, age is 42, collateral is 2000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 5, savings is 0","- sex : 1
123
+ - amnt req : 2000
124
+ - maturity : 60.0
125
+ - assets val : 2800
126
+ - dec profit : 320.0
127
+ - xperience : 12.0
128
+ - educatn : 3
129
+ - age : 42
130
+ - collateral : 2000
131
+ - locatn : 0
132
+ - guarantor : 0
133
+ - relatnshp : 0
134
+ - purpose : 1
135
+ - sector : 5
136
+ - savings : 0",The sex is 1. The amnt req is 2000. The maturity is 60.0. The assets val is 2800. The dec profit is 320.0. The xperience is 12.0. The educatn is 3. The age is 42. The collateral is 2000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 5. The savings is 0,"<table border=""1"" class=""dataframe"">
137
+ <thead>
138
+ <tr style=""text-align: right;"">
139
+ <th></th>
140
+ <th>sex</th>
141
+ <th>amnt req</th>
142
+ <th>maturity</th>
143
+ <th>assets val</th>
144
+ <th>dec profit</th>
145
+ <th>xperience</th>
146
+ <th>educatn</th>
147
+ <th>age</th>
148
+ <th>collateral</th>
149
+ <th>locatn</th>
150
+ <th>guarantor</th>
151
+ <th>relatnshp</th>
152
+ <th>purpose</th>
153
+ <th>sector</th>
154
+ <th>savings</th>
155
+ </tr>
156
+ </thead>
157
+ <tbody>
158
+ <tr>
159
+ <th>0</th>
160
+ <td>1</td>
161
+ <td>2000</td>
162
+ <td>60.0</td>
163
+ <td>2800</td>
164
+ <td>320.0</td>
165
+ <td>12.0</td>
166
+ <td>3</td>
167
+ <td>42</td>
168
+ <td>2000</td>
169
+ <td>0</td>
170
+ <td>0</td>
171
+ <td>0</td>
172
+ <td>1</td>
173
+ <td>5</td>
174
+ <td>0</td>
175
+ </tr>
176
+ </tbody>
177
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
178
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
179
+ 0 & 1 & 2000 & 60.000000 & 2800 & 320.000000 & 12.000000 & 3 & 42 & 2000 & 0 & 0 & 0 & 1 & 5 & 0 \\
180
+ \end{tabular}
181
+ ","{'age': 42, 'amnt req': 2000, 'assets val': 2800, 'collateral': 2000, 'dec profit': 320.0, 'educatn': 3, 'guarantor': 0, 'locatn': 0, 'maturity': 60.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 5, 'sex': 1, 'xperience': 12.0}",A 42-year-old male is applying for a loan of 2000 cedis. The applicant works in service sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 60.0 years. His assets value is 2800 cedis and his declared profits (after tax) is 320.0 cedis. His educational background is primary and the number of years that he has been in business is 12.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 2000 cedis.
182
+ 2,0,5000,3000,1,40.0,7000,1350.0,5.0,3,35,2000,0,0,1,1,4,0,No,"sex is 0, amnt req is 5000, maturity is 40.0, assets val is 7000, dec profit is 1350.0, xperience is 5.0, educatn is 3, age is 35, collateral is 2000, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 1, sector is 4, savings is 0","- sex : 0
183
+ - amnt req : 5000
184
+ - maturity : 40.0
185
+ - assets val : 7000
186
+ - dec profit : 1350.0
187
+ - xperience : 5.0
188
+ - educatn : 3
189
+ - age : 35
190
+ - collateral : 2000
191
+ - locatn : 0
192
+ - guarantor : 0
193
+ - relatnshp : 1
194
+ - purpose : 1
195
+ - sector : 4
196
+ - savings : 0",The sex is 0. The amnt req is 5000. The maturity is 40.0. The assets val is 7000. The dec profit is 1350.0. The xperience is 5.0. The educatn is 3. The age is 35. The collateral is 2000. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 1. The sector is 4. The savings is 0,"<table border=""1"" class=""dataframe"">
197
+ <thead>
198
+ <tr style=""text-align: right;"">
199
+ <th></th>
200
+ <th>sex</th>
201
+ <th>amnt req</th>
202
+ <th>maturity</th>
203
+ <th>assets val</th>
204
+ <th>dec profit</th>
205
+ <th>xperience</th>
206
+ <th>educatn</th>
207
+ <th>age</th>
208
+ <th>collateral</th>
209
+ <th>locatn</th>
210
+ <th>guarantor</th>
211
+ <th>relatnshp</th>
212
+ <th>purpose</th>
213
+ <th>sector</th>
214
+ <th>savings</th>
215
+ </tr>
216
+ </thead>
217
+ <tbody>
218
+ <tr>
219
+ <th>0</th>
220
+ <td>0</td>
221
+ <td>5000</td>
222
+ <td>40.0</td>
223
+ <td>7000</td>
224
+ <td>1350.0</td>
225
+ <td>5.0</td>
226
+ <td>3</td>
227
+ <td>35</td>
228
+ <td>2000</td>
229
+ <td>0</td>
230
+ <td>0</td>
231
+ <td>1</td>
232
+ <td>1</td>
233
+ <td>4</td>
234
+ <td>0</td>
235
+ </tr>
236
+ </tbody>
237
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
238
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
239
+ 0 & 0 & 5000 & 40.000000 & 7000 & 1350.000000 & 5.000000 & 3 & 35 & 2000 & 0 & 0 & 1 & 1 & 4 & 0 \\
240
+ \end{tabular}
241
+ ","{'age': 35, 'amnt req': 5000, 'assets val': 7000, 'collateral': 2000, 'dec profit': 1350.0, 'educatn': 3, 'guarantor': 0, 'locatn': 0, 'maturity': 40.0, 'purpose': 1, 'relatnshp': 1, 'savings': 0, 'sector': 4, 'sex': 0, 'xperience': 5.0}",A 35-year-old female is applying for a loan of 5000 cedis. The applicant works in agriculture sector and the purpose of the loan is not related to her business. The maturity period of the requested loan is 40.0 years. Her assets value is 7000 cedis and her declared profits (after tax) is 1350.0 cedis. Her educational background is primary and the number of years that she has been in business is 5.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 2000 cedis.
242
+ 6,1,1000,500,1,60.0,1000,120.0,8.0,3,56,1000,1,0,0,0,5,0,No,"sex is 1, amnt req is 1000, maturity is 60.0, assets val is 1000, dec profit is 120.0, xperience is 8.0, educatn is 3, age is 56, collateral is 1000, locatn is 1, guarantor is 0, relatnshp is 0, purpose is 0, sector is 5, savings is 0","- sex : 1
243
+ - amnt req : 1000
244
+ - maturity : 60.0
245
+ - assets val : 1000
246
+ - dec profit : 120.0
247
+ - xperience : 8.0
248
+ - educatn : 3
249
+ - age : 56
250
+ - collateral : 1000
251
+ - locatn : 1
252
+ - guarantor : 0
253
+ - relatnshp : 0
254
+ - purpose : 0
255
+ - sector : 5
256
+ - savings : 0",The sex is 1. The amnt req is 1000. The maturity is 60.0. The assets val is 1000. The dec profit is 120.0. The xperience is 8.0. The educatn is 3. The age is 56. The collateral is 1000. The locatn is 1. The guarantor is 0. The relatnshp is 0. The purpose is 0. The sector is 5. The savings is 0,"<table border=""1"" class=""dataframe"">
257
+ <thead>
258
+ <tr style=""text-align: right;"">
259
+ <th></th>
260
+ <th>sex</th>
261
+ <th>amnt req</th>
262
+ <th>maturity</th>
263
+ <th>assets val</th>
264
+ <th>dec profit</th>
265
+ <th>xperience</th>
266
+ <th>educatn</th>
267
+ <th>age</th>
268
+ <th>collateral</th>
269
+ <th>locatn</th>
270
+ <th>guarantor</th>
271
+ <th>relatnshp</th>
272
+ <th>purpose</th>
273
+ <th>sector</th>
274
+ <th>savings</th>
275
+ </tr>
276
+ </thead>
277
+ <tbody>
278
+ <tr>
279
+ <th>0</th>
280
+ <td>1</td>
281
+ <td>1000</td>
282
+ <td>60.0</td>
283
+ <td>1000</td>
284
+ <td>120.0</td>
285
+ <td>8.0</td>
286
+ <td>3</td>
287
+ <td>56</td>
288
+ <td>1000</td>
289
+ <td>1</td>
290
+ <td>0</td>
291
+ <td>0</td>
292
+ <td>0</td>
293
+ <td>5</td>
294
+ <td>0</td>
295
+ </tr>
296
+ </tbody>
297
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
298
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
299
+ 0 & 1 & 1000 & 60.000000 & 1000 & 120.000000 & 8.000000 & 3 & 56 & 1000 & 1 & 0 & 0 & 0 & 5 & 0 \\
300
+ \end{tabular}
301
+ ","{'age': 56, 'amnt req': 1000, 'assets val': 1000, 'collateral': 1000, 'dec profit': 120.0, 'educatn': 3, 'guarantor': 0, 'locatn': 1, 'maturity': 60.0, 'purpose': 0, 'relatnshp': 0, 'savings': 0, 'sector': 5, 'sex': 1, 'xperience': 8.0}",A 56-year-old male is applying for a loan of 1000 cedis. The applicant works in service sector and the purpose of the loan is related to his business. The maturity period of the requested loan is 60.0 years. His assets value is 1000 cedis and his declared profits (after tax) is 120.0 cedis. His educational background is primary and the number of years that he has been in business is 8.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He resides or have his business close to the bank. The value of his collateral is 1000 cedis.
302
+ 3,0,1000,1000,0,24.0,2500,590.0,6.0,1,25,20000,1,0,1,0,1,0,Yes,"sex is 0, amnt req is 1000, maturity is 24.0, assets val is 2500, dec profit is 590.0, xperience is 6.0, educatn is 1, age is 25, collateral is 20000, locatn is 1, guarantor is 0, relatnshp is 1, purpose is 0, sector is 1, savings is 0","- sex : 0
303
+ - amnt req : 1000
304
+ - maturity : 24.0
305
+ - assets val : 2500
306
+ - dec profit : 590.0
307
+ - xperience : 6.0
308
+ - educatn : 1
309
+ - age : 25
310
+ - collateral : 20000
311
+ - locatn : 1
312
+ - guarantor : 0
313
+ - relatnshp : 1
314
+ - purpose : 0
315
+ - sector : 1
316
+ - savings : 0",The sex is 0. The amnt req is 1000. The maturity is 24.0. The assets val is 2500. The dec profit is 590.0. The xperience is 6.0. The educatn is 1. The age is 25. The collateral is 20000. The locatn is 1. The guarantor is 0. The relatnshp is 1. The purpose is 0. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
317
+ <thead>
318
+ <tr style=""text-align: right;"">
319
+ <th></th>
320
+ <th>sex</th>
321
+ <th>amnt req</th>
322
+ <th>maturity</th>
323
+ <th>assets val</th>
324
+ <th>dec profit</th>
325
+ <th>xperience</th>
326
+ <th>educatn</th>
327
+ <th>age</th>
328
+ <th>collateral</th>
329
+ <th>locatn</th>
330
+ <th>guarantor</th>
331
+ <th>relatnshp</th>
332
+ <th>purpose</th>
333
+ <th>sector</th>
334
+ <th>savings</th>
335
+ </tr>
336
+ </thead>
337
+ <tbody>
338
+ <tr>
339
+ <th>0</th>
340
+ <td>0</td>
341
+ <td>1000</td>
342
+ <td>24.0</td>
343
+ <td>2500</td>
344
+ <td>590.0</td>
345
+ <td>6.0</td>
346
+ <td>1</td>
347
+ <td>25</td>
348
+ <td>20000</td>
349
+ <td>1</td>
350
+ <td>0</td>
351
+ <td>1</td>
352
+ <td>0</td>
353
+ <td>1</td>
354
+ <td>0</td>
355
+ </tr>
356
+ </tbody>
357
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
358
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
359
+ 0 & 0 & 1000 & 24.000000 & 2500 & 590.000000 & 6.000000 & 1 & 25 & 20000 & 1 & 0 & 1 & 0 & 1 & 0 \\
360
+ \end{tabular}
361
+ ","{'age': 25, 'amnt req': 1000, 'assets val': 2500, 'collateral': 20000, 'dec profit': 590.0, 'educatn': 1, 'guarantor': 0, 'locatn': 1, 'maturity': 24.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 1, 'sex': 0, 'xperience': 6.0}",A 25-year-old female is applying for a loan of 1000 cedis. The applicant works in commerce sector and the purpose of the loan is related to her business. The maturity period of the requested loan is 24.0 years. Her assets value is 2500 cedis and her declared profits (after tax) is 590.0 cedis. Her educational background is tertiary and the number of years that she has been in business is 6.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She resides or have her business close to the bank. The value of her collateral is 20000 cedis.
362
+ 7,1,12000,10000,1,30.0,10000,560.0,2.0,3,38,9000,1,1,1,0,4,0,No,"sex is 1, amnt req is 12000, maturity is 30.0, assets val is 10000, dec profit is 560.0, xperience is 2.0, educatn is 3, age is 38, collateral is 9000, locatn is 1, guarantor is 1, relatnshp is 1, purpose is 0, sector is 4, savings is 0","- sex : 1
363
+ - amnt req : 12000
364
+ - maturity : 30.0
365
+ - assets val : 10000
366
+ - dec profit : 560.0
367
+ - xperience : 2.0
368
+ - educatn : 3
369
+ - age : 38
370
+ - collateral : 9000
371
+ - locatn : 1
372
+ - guarantor : 1
373
+ - relatnshp : 1
374
+ - purpose : 0
375
+ - sector : 4
376
+ - savings : 0",The sex is 1. The amnt req is 12000. The maturity is 30.0. The assets val is 10000. The dec profit is 560.0. The xperience is 2.0. The educatn is 3. The age is 38. The collateral is 9000. The locatn is 1. The guarantor is 1. The relatnshp is 1. The purpose is 0. The sector is 4. The savings is 0,"<table border=""1"" class=""dataframe"">
377
+ <thead>
378
+ <tr style=""text-align: right;"">
379
+ <th></th>
380
+ <th>sex</th>
381
+ <th>amnt req</th>
382
+ <th>maturity</th>
383
+ <th>assets val</th>
384
+ <th>dec profit</th>
385
+ <th>xperience</th>
386
+ <th>educatn</th>
387
+ <th>age</th>
388
+ <th>collateral</th>
389
+ <th>locatn</th>
390
+ <th>guarantor</th>
391
+ <th>relatnshp</th>
392
+ <th>purpose</th>
393
+ <th>sector</th>
394
+ <th>savings</th>
395
+ </tr>
396
+ </thead>
397
+ <tbody>
398
+ <tr>
399
+ <th>0</th>
400
+ <td>1</td>
401
+ <td>12000</td>
402
+ <td>30.0</td>
403
+ <td>10000</td>
404
+ <td>560.0</td>
405
+ <td>2.0</td>
406
+ <td>3</td>
407
+ <td>38</td>
408
+ <td>9000</td>
409
+ <td>1</td>
410
+ <td>1</td>
411
+ <td>1</td>
412
+ <td>0</td>
413
+ <td>4</td>
414
+ <td>0</td>
415
+ </tr>
416
+ </tbody>
417
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
418
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
419
+ 0 & 1 & 12000 & 30.000000 & 10000 & 560.000000 & 2.000000 & 3 & 38 & 9000 & 1 & 1 & 1 & 0 & 4 & 0 \\
420
+ \end{tabular}
421
+ ","{'age': 38, 'amnt req': 12000, 'assets val': 10000, 'collateral': 9000, 'dec profit': 560.0, 'educatn': 3, 'guarantor': 1, 'locatn': 1, 'maturity': 30.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 4, 'sex': 1, 'xperience': 2.0}",A 38-year-old male is applying for a loan of 12000 cedis. The applicant works in agriculture sector and the purpose of the loan is related to his business. The maturity period of the requested loan is 30.0 years. His assets value is 10000 cedis and his declared profits (after tax) is 560.0 cedis. His educational background is primary and the number of years that he has been in business is 2.0. He provided a guarantor and this is his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He resides or have his business close to the bank. The value of his collateral is 9000 cedis.
422
+ 5,0,9000,9000,0,30.0,5000,320.0,9.0,4,38,9000,1,1,1,1,1,1,Yes,"sex is 0, amnt req is 9000, maturity is 30.0, assets val is 5000, dec profit is 320.0, xperience is 9.0, educatn is 4, age is 38, collateral is 9000, locatn is 1, guarantor is 1, relatnshp is 1, purpose is 1, sector is 1, savings is 1","- sex : 0
423
+ - amnt req : 9000
424
+ - maturity : 30.0
425
+ - assets val : 5000
426
+ - dec profit : 320.0
427
+ - xperience : 9.0
428
+ - educatn : 4
429
+ - age : 38
430
+ - collateral : 9000
431
+ - locatn : 1
432
+ - guarantor : 1
433
+ - relatnshp : 1
434
+ - purpose : 1
435
+ - sector : 1
436
+ - savings : 1",The sex is 0. The amnt req is 9000. The maturity is 30.0. The assets val is 5000. The dec profit is 320.0. The xperience is 9.0. The educatn is 4. The age is 38. The collateral is 9000. The locatn is 1. The guarantor is 1. The relatnshp is 1. The purpose is 1. The sector is 1. The savings is 1,"<table border=""1"" class=""dataframe"">
437
+ <thead>
438
+ <tr style=""text-align: right;"">
439
+ <th></th>
440
+ <th>sex</th>
441
+ <th>amnt req</th>
442
+ <th>maturity</th>
443
+ <th>assets val</th>
444
+ <th>dec profit</th>
445
+ <th>xperience</th>
446
+ <th>educatn</th>
447
+ <th>age</th>
448
+ <th>collateral</th>
449
+ <th>locatn</th>
450
+ <th>guarantor</th>
451
+ <th>relatnshp</th>
452
+ <th>purpose</th>
453
+ <th>sector</th>
454
+ <th>savings</th>
455
+ </tr>
456
+ </thead>
457
+ <tbody>
458
+ <tr>
459
+ <th>0</th>
460
+ <td>0</td>
461
+ <td>9000</td>
462
+ <td>30.0</td>
463
+ <td>5000</td>
464
+ <td>320.0</td>
465
+ <td>9.0</td>
466
+ <td>4</td>
467
+ <td>38</td>
468
+ <td>9000</td>
469
+ <td>1</td>
470
+ <td>1</td>
471
+ <td>1</td>
472
+ <td>1</td>
473
+ <td>1</td>
474
+ <td>1</td>
475
+ </tr>
476
+ </tbody>
477
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
478
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
479
+ 0 & 0 & 9000 & 30.000000 & 5000 & 320.000000 & 9.000000 & 4 & 38 & 9000 & 1 & 1 & 1 & 1 & 1 & 1 \\
480
+ \end{tabular}
481
+ ","{'age': 38, 'amnt req': 9000, 'assets val': 5000, 'collateral': 9000, 'dec profit': 320.0, 'educatn': 4, 'guarantor': 1, 'locatn': 1, 'maturity': 30.0, 'purpose': 1, 'relatnshp': 1, 'savings': 1, 'sector': 1, 'sex': 0, 'xperience': 9.0}",A 38-year-old female is applying for a loan of 9000 cedis. The applicant works in commerce sector and the purpose of the loan is not related to her business. The maturity period of the requested loan is 30.0 years. Her assets value is 5000 cedis and her declared profits (after tax) is 320.0 cedis. Her educational background is illiterate and the number of years that she has been in business is 9.0. She provided a guarantor and this is her first time requesting for a loan at the bank. She has non-mandatory savings with the bank. She resides or have her business close to the bank. The value of her collateral is 9000 cedis.
new_data/ghana-fewshot.csv ADDED
@@ -0,0 +1,601 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Unnamed: 0,sex,amnt req,amnt grnt,ration,maturity,assets val,dec profit,xperience,educatn,age,collateral,locatn,guarantor,relatnshp,purpose,sector,savings,target,great,list,text,html,latex,json,LIFT
2
+ 0,0,2000,2000,0,36.0,4000,500.0,3.0,1,28,900,0,0,1,0,1,0,Yes,"sex is 0, amnt req is 2000, maturity is 36.0, assets val is 4000, dec profit is 500.0, xperience is 3.0, educatn is 1, age is 28, collateral is 900, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 0, sector is 1, savings is 0","- sex : 0
3
+ - amnt req : 2000
4
+ - maturity : 36.0
5
+ - assets val : 4000
6
+ - dec profit : 500.0
7
+ - xperience : 3.0
8
+ - educatn : 1
9
+ - age : 28
10
+ - collateral : 900
11
+ - locatn : 0
12
+ - guarantor : 0
13
+ - relatnshp : 1
14
+ - purpose : 0
15
+ - sector : 1
16
+ - savings : 0",The sex is 0. The amnt req is 2000. The maturity is 36.0. The assets val is 4000. The dec profit is 500.0. The xperience is 3.0. The educatn is 1. The age is 28. The collateral is 900. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 0. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
17
+ <thead>
18
+ <tr style=""text-align: right;"">
19
+ <th></th>
20
+ <th>sex</th>
21
+ <th>amnt req</th>
22
+ <th>maturity</th>
23
+ <th>assets val</th>
24
+ <th>dec profit</th>
25
+ <th>xperience</th>
26
+ <th>educatn</th>
27
+ <th>age</th>
28
+ <th>collateral</th>
29
+ <th>locatn</th>
30
+ <th>guarantor</th>
31
+ <th>relatnshp</th>
32
+ <th>purpose</th>
33
+ <th>sector</th>
34
+ <th>savings</th>
35
+ </tr>
36
+ </thead>
37
+ <tbody>
38
+ <tr>
39
+ <th>0</th>
40
+ <td>0</td>
41
+ <td>2000</td>
42
+ <td>36.0</td>
43
+ <td>4000</td>
44
+ <td>500.0</td>
45
+ <td>3.0</td>
46
+ <td>1</td>
47
+ <td>28</td>
48
+ <td>900</td>
49
+ <td>0</td>
50
+ <td>0</td>
51
+ <td>1</td>
52
+ <td>0</td>
53
+ <td>1</td>
54
+ <td>0</td>
55
+ </tr>
56
+ </tbody>
57
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
58
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
59
+ 0 & 0 & 2000 & 36.000000 & 4000 & 500.000000 & 3.000000 & 1 & 28 & 900 & 0 & 0 & 1 & 0 & 1 & 0 \\
60
+ \end{tabular}
61
+ ","{'age': 28, 'amnt req': 2000, 'assets val': 4000, 'collateral': 900, 'dec profit': 500.0, 'educatn': 1, 'guarantor': 0, 'locatn': 0, 'maturity': 36.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 1, 'sex': 0, 'xperience': 3.0}",A 28-year-old female is applying for a loan of 2000 cedis. The applicant works in commerce sector and the purpose of the loan is related to her business. The maturity period of the requested loan is 36.0 years. Her assets value is 4000 cedis and her declared profits (after tax) is 500.0 cedis. Her educational background is tertiary and the number of years that she has been in business is 3.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 900 cedis.
62
+ 1,1,1000,1000,0,30.0,3000,600.0,6.0,2,35,3000,0,0,0,1,1,0,Yes,"sex is 1, amnt req is 1000, maturity is 30.0, assets val is 3000, dec profit is 600.0, xperience is 6.0, educatn is 2, age is 35, collateral is 3000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 1, savings is 0","- sex : 1
63
+ - amnt req : 1000
64
+ - maturity : 30.0
65
+ - assets val : 3000
66
+ - dec profit : 600.0
67
+ - xperience : 6.0
68
+ - educatn : 2
69
+ - age : 35
70
+ - collateral : 3000
71
+ - locatn : 0
72
+ - guarantor : 0
73
+ - relatnshp : 0
74
+ - purpose : 1
75
+ - sector : 1
76
+ - savings : 0",The sex is 1. The amnt req is 1000. The maturity is 30.0. The assets val is 3000. The dec profit is 600.0. The xperience is 6.0. The educatn is 2. The age is 35. The collateral is 3000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
77
+ <thead>
78
+ <tr style=""text-align: right;"">
79
+ <th></th>
80
+ <th>sex</th>
81
+ <th>amnt req</th>
82
+ <th>maturity</th>
83
+ <th>assets val</th>
84
+ <th>dec profit</th>
85
+ <th>xperience</th>
86
+ <th>educatn</th>
87
+ <th>age</th>
88
+ <th>collateral</th>
89
+ <th>locatn</th>
90
+ <th>guarantor</th>
91
+ <th>relatnshp</th>
92
+ <th>purpose</th>
93
+ <th>sector</th>
94
+ <th>savings</th>
95
+ </tr>
96
+ </thead>
97
+ <tbody>
98
+ <tr>
99
+ <th>0</th>
100
+ <td>1</td>
101
+ <td>1000</td>
102
+ <td>30.0</td>
103
+ <td>3000</td>
104
+ <td>600.0</td>
105
+ <td>6.0</td>
106
+ <td>2</td>
107
+ <td>35</td>
108
+ <td>3000</td>
109
+ <td>0</td>
110
+ <td>0</td>
111
+ <td>0</td>
112
+ <td>1</td>
113
+ <td>1</td>
114
+ <td>0</td>
115
+ </tr>
116
+ </tbody>
117
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
118
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
119
+ 0 & 1 & 1000 & 30.000000 & 3000 & 600.000000 & 6.000000 & 2 & 35 & 3000 & 0 & 0 & 0 & 1 & 1 & 0 \\
120
+ \end{tabular}
121
+ ","{'age': 35, 'amnt req': 1000, 'assets val': 3000, 'collateral': 3000, 'dec profit': 600.0, 'educatn': 2, 'guarantor': 0, 'locatn': 0, 'maturity': 30.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 1, 'sex': 1, 'xperience': 6.0}",A 35-year-old male is applying for a loan of 1000 cedis. The applicant works in commerce sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 30.0 years. His assets value is 3000 cedis and his declared profits (after tax) is 600.0 cedis. His educational background is secondary and the number of years that he has been in business is 6.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 3000 cedis.
122
+ 2,0,5000,3000,1,40.0,7000,1350.0,5.0,3,35,2000,0,0,1,1,4,0,No,"sex is 0, amnt req is 5000, maturity is 40.0, assets val is 7000, dec profit is 1350.0, xperience is 5.0, educatn is 3, age is 35, collateral is 2000, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 1, sector is 4, savings is 0","- sex : 0
123
+ - amnt req : 5000
124
+ - maturity : 40.0
125
+ - assets val : 7000
126
+ - dec profit : 1350.0
127
+ - xperience : 5.0
128
+ - educatn : 3
129
+ - age : 35
130
+ - collateral : 2000
131
+ - locatn : 0
132
+ - guarantor : 0
133
+ - relatnshp : 1
134
+ - purpose : 1
135
+ - sector : 4
136
+ - savings : 0",The sex is 0. The amnt req is 5000. The maturity is 40.0. The assets val is 7000. The dec profit is 1350.0. The xperience is 5.0. The educatn is 3. The age is 35. The collateral is 2000. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 1. The sector is 4. The savings is 0,"<table border=""1"" class=""dataframe"">
137
+ <thead>
138
+ <tr style=""text-align: right;"">
139
+ <th></th>
140
+ <th>sex</th>
141
+ <th>amnt req</th>
142
+ <th>maturity</th>
143
+ <th>assets val</th>
144
+ <th>dec profit</th>
145
+ <th>xperience</th>
146
+ <th>educatn</th>
147
+ <th>age</th>
148
+ <th>collateral</th>
149
+ <th>locatn</th>
150
+ <th>guarantor</th>
151
+ <th>relatnshp</th>
152
+ <th>purpose</th>
153
+ <th>sector</th>
154
+ <th>savings</th>
155
+ </tr>
156
+ </thead>
157
+ <tbody>
158
+ <tr>
159
+ <th>0</th>
160
+ <td>0</td>
161
+ <td>5000</td>
162
+ <td>40.0</td>
163
+ <td>7000</td>
164
+ <td>1350.0</td>
165
+ <td>5.0</td>
166
+ <td>3</td>
167
+ <td>35</td>
168
+ <td>2000</td>
169
+ <td>0</td>
170
+ <td>0</td>
171
+ <td>1</td>
172
+ <td>1</td>
173
+ <td>4</td>
174
+ <td>0</td>
175
+ </tr>
176
+ </tbody>
177
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
178
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
179
+ 0 & 0 & 5000 & 40.000000 & 7000 & 1350.000000 & 5.000000 & 3 & 35 & 2000 & 0 & 0 & 1 & 1 & 4 & 0 \\
180
+ \end{tabular}
181
+ ","{'age': 35, 'amnt req': 5000, 'assets val': 7000, 'collateral': 2000, 'dec profit': 1350.0, 'educatn': 3, 'guarantor': 0, 'locatn': 0, 'maturity': 40.0, 'purpose': 1, 'relatnshp': 1, 'savings': 0, 'sector': 4, 'sex': 0, 'xperience': 5.0}",A 35-year-old female is applying for a loan of 5000 cedis. The applicant works in agriculture sector and the purpose of the loan is not related to her business. The maturity period of the requested loan is 40.0 years. Her assets value is 7000 cedis and her declared profits (after tax) is 1350.0 cedis. Her educational background is primary and the number of years that she has been in business is 5.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 2000 cedis.
182
+ 4,1,2000,2000,0,60.0,2800,320.0,12.0,3,42,2000,0,0,0,1,5,0,Yes,"sex is 1, amnt req is 2000, maturity is 60.0, assets val is 2800, dec profit is 320.0, xperience is 12.0, educatn is 3, age is 42, collateral is 2000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 5, savings is 0","- sex : 1
183
+ - amnt req : 2000
184
+ - maturity : 60.0
185
+ - assets val : 2800
186
+ - dec profit : 320.0
187
+ - xperience : 12.0
188
+ - educatn : 3
189
+ - age : 42
190
+ - collateral : 2000
191
+ - locatn : 0
192
+ - guarantor : 0
193
+ - relatnshp : 0
194
+ - purpose : 1
195
+ - sector : 5
196
+ - savings : 0",The sex is 1. The amnt req is 2000. The maturity is 60.0. The assets val is 2800. The dec profit is 320.0. The xperience is 12.0. The educatn is 3. The age is 42. The collateral is 2000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 5. The savings is 0,"<table border=""1"" class=""dataframe"">
197
+ <thead>
198
+ <tr style=""text-align: right;"">
199
+ <th></th>
200
+ <th>sex</th>
201
+ <th>amnt req</th>
202
+ <th>maturity</th>
203
+ <th>assets val</th>
204
+ <th>dec profit</th>
205
+ <th>xperience</th>
206
+ <th>educatn</th>
207
+ <th>age</th>
208
+ <th>collateral</th>
209
+ <th>locatn</th>
210
+ <th>guarantor</th>
211
+ <th>relatnshp</th>
212
+ <th>purpose</th>
213
+ <th>sector</th>
214
+ <th>savings</th>
215
+ </tr>
216
+ </thead>
217
+ <tbody>
218
+ <tr>
219
+ <th>0</th>
220
+ <td>1</td>
221
+ <td>2000</td>
222
+ <td>60.0</td>
223
+ <td>2800</td>
224
+ <td>320.0</td>
225
+ <td>12.0</td>
226
+ <td>3</td>
227
+ <td>42</td>
228
+ <td>2000</td>
229
+ <td>0</td>
230
+ <td>0</td>
231
+ <td>0</td>
232
+ <td>1</td>
233
+ <td>5</td>
234
+ <td>0</td>
235
+ </tr>
236
+ </tbody>
237
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
238
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
239
+ 0 & 1 & 2000 & 60.000000 & 2800 & 320.000000 & 12.000000 & 3 & 42 & 2000 & 0 & 0 & 0 & 1 & 5 & 0 \\
240
+ \end{tabular}
241
+ ","{'age': 42, 'amnt req': 2000, 'assets val': 2800, 'collateral': 2000, 'dec profit': 320.0, 'educatn': 3, 'guarantor': 0, 'locatn': 0, 'maturity': 60.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 5, 'sex': 1, 'xperience': 12.0}",A 42-year-old male is applying for a loan of 2000 cedis. The applicant works in service sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 60.0 years. His assets value is 2800 cedis and his declared profits (after tax) is 320.0 cedis. His educational background is primary and the number of years that he has been in business is 12.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 2000 cedis.
242
+ 3,0,1000,1000,0,24.0,2500,590.0,6.0,1,25,20000,1,0,1,0,1,0,Yes,"sex is 0, amnt req is 1000, maturity is 24.0, assets val is 2500, dec profit is 590.0, xperience is 6.0, educatn is 1, age is 25, collateral is 20000, locatn is 1, guarantor is 0, relatnshp is 1, purpose is 0, sector is 1, savings is 0","- sex : 0
243
+ - amnt req : 1000
244
+ - maturity : 24.0
245
+ - assets val : 2500
246
+ - dec profit : 590.0
247
+ - xperience : 6.0
248
+ - educatn : 1
249
+ - age : 25
250
+ - collateral : 20000
251
+ - locatn : 1
252
+ - guarantor : 0
253
+ - relatnshp : 1
254
+ - purpose : 0
255
+ - sector : 1
256
+ - savings : 0",The sex is 0. The amnt req is 1000. The maturity is 24.0. The assets val is 2500. The dec profit is 590.0. The xperience is 6.0. The educatn is 1. The age is 25. The collateral is 20000. The locatn is 1. The guarantor is 0. The relatnshp is 1. The purpose is 0. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
257
+ <thead>
258
+ <tr style=""text-align: right;"">
259
+ <th></th>
260
+ <th>sex</th>
261
+ <th>amnt req</th>
262
+ <th>maturity</th>
263
+ <th>assets val</th>
264
+ <th>dec profit</th>
265
+ <th>xperience</th>
266
+ <th>educatn</th>
267
+ <th>age</th>
268
+ <th>collateral</th>
269
+ <th>locatn</th>
270
+ <th>guarantor</th>
271
+ <th>relatnshp</th>
272
+ <th>purpose</th>
273
+ <th>sector</th>
274
+ <th>savings</th>
275
+ </tr>
276
+ </thead>
277
+ <tbody>
278
+ <tr>
279
+ <th>0</th>
280
+ <td>0</td>
281
+ <td>1000</td>
282
+ <td>24.0</td>
283
+ <td>2500</td>
284
+ <td>590.0</td>
285
+ <td>6.0</td>
286
+ <td>1</td>
287
+ <td>25</td>
288
+ <td>20000</td>
289
+ <td>1</td>
290
+ <td>0</td>
291
+ <td>1</td>
292
+ <td>0</td>
293
+ <td>1</td>
294
+ <td>0</td>
295
+ </tr>
296
+ </tbody>
297
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
298
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
299
+ 0 & 0 & 1000 & 24.000000 & 2500 & 590.000000 & 6.000000 & 1 & 25 & 20000 & 1 & 0 & 1 & 0 & 1 & 0 \\
300
+ \end{tabular}
301
+ ","{'age': 25, 'amnt req': 1000, 'assets val': 2500, 'collateral': 20000, 'dec profit': 590.0, 'educatn': 1, 'guarantor': 0, 'locatn': 1, 'maturity': 24.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 1, 'sex': 0, 'xperience': 6.0}",A 25-year-old female is applying for a loan of 1000 cedis. The applicant works in commerce sector and the purpose of the loan is related to her business. The maturity period of the requested loan is 24.0 years. Her assets value is 2500 cedis and her declared profits (after tax) is 590.0 cedis. Her educational background is tertiary and the number of years that she has been in business is 6.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She resides or have her business close to the bank. The value of her collateral is 20000 cedis.
302
+ 6,1,1000,500,1,60.0,1000,120.0,8.0,3,56,1000,1,0,0,0,5,0,No,"sex is 1, amnt req is 1000, maturity is 60.0, assets val is 1000, dec profit is 120.0, xperience is 8.0, educatn is 3, age is 56, collateral is 1000, locatn is 1, guarantor is 0, relatnshp is 0, purpose is 0, sector is 5, savings is 0","- sex : 1
303
+ - amnt req : 1000
304
+ - maturity : 60.0
305
+ - assets val : 1000
306
+ - dec profit : 120.0
307
+ - xperience : 8.0
308
+ - educatn : 3
309
+ - age : 56
310
+ - collateral : 1000
311
+ - locatn : 1
312
+ - guarantor : 0
313
+ - relatnshp : 0
314
+ - purpose : 0
315
+ - sector : 5
316
+ - savings : 0",The sex is 1. The amnt req is 1000. The maturity is 60.0. The assets val is 1000. The dec profit is 120.0. The xperience is 8.0. The educatn is 3. The age is 56. The collateral is 1000. The locatn is 1. The guarantor is 0. The relatnshp is 0. The purpose is 0. The sector is 5. The savings is 0,"<table border=""1"" class=""dataframe"">
317
+ <thead>
318
+ <tr style=""text-align: right;"">
319
+ <th></th>
320
+ <th>sex</th>
321
+ <th>amnt req</th>
322
+ <th>maturity</th>
323
+ <th>assets val</th>
324
+ <th>dec profit</th>
325
+ <th>xperience</th>
326
+ <th>educatn</th>
327
+ <th>age</th>
328
+ <th>collateral</th>
329
+ <th>locatn</th>
330
+ <th>guarantor</th>
331
+ <th>relatnshp</th>
332
+ <th>purpose</th>
333
+ <th>sector</th>
334
+ <th>savings</th>
335
+ </tr>
336
+ </thead>
337
+ <tbody>
338
+ <tr>
339
+ <th>0</th>
340
+ <td>1</td>
341
+ <td>1000</td>
342
+ <td>60.0</td>
343
+ <td>1000</td>
344
+ <td>120.0</td>
345
+ <td>8.0</td>
346
+ <td>3</td>
347
+ <td>56</td>
348
+ <td>1000</td>
349
+ <td>1</td>
350
+ <td>0</td>
351
+ <td>0</td>
352
+ <td>0</td>
353
+ <td>5</td>
354
+ <td>0</td>
355
+ </tr>
356
+ </tbody>
357
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
358
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
359
+ 0 & 1 & 1000 & 60.000000 & 1000 & 120.000000 & 8.000000 & 3 & 56 & 1000 & 1 & 0 & 0 & 0 & 5 & 0 \\
360
+ \end{tabular}
361
+ ","{'age': 56, 'amnt req': 1000, 'assets val': 1000, 'collateral': 1000, 'dec profit': 120.0, 'educatn': 3, 'guarantor': 0, 'locatn': 1, 'maturity': 60.0, 'purpose': 0, 'relatnshp': 0, 'savings': 0, 'sector': 5, 'sex': 1, 'xperience': 8.0}",A 56-year-old male is applying for a loan of 1000 cedis. The applicant works in service sector and the purpose of the loan is related to his business. The maturity period of the requested loan is 60.0 years. His assets value is 1000 cedis and his declared profits (after tax) is 120.0 cedis. His educational background is primary and the number of years that he has been in business is 8.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He resides or have his business close to the bank. The value of his collateral is 1000 cedis.
362
+ 5,0,9000,9000,0,30.0,5000,320.0,9.0,4,38,9000,1,1,1,1,1,1,Yes,"sex is 0, amnt req is 9000, maturity is 30.0, assets val is 5000, dec profit is 320.0, xperience is 9.0, educatn is 4, age is 38, collateral is 9000, locatn is 1, guarantor is 1, relatnshp is 1, purpose is 1, sector is 1, savings is 1","- sex : 0
363
+ - amnt req : 9000
364
+ - maturity : 30.0
365
+ - assets val : 5000
366
+ - dec profit : 320.0
367
+ - xperience : 9.0
368
+ - educatn : 4
369
+ - age : 38
370
+ - collateral : 9000
371
+ - locatn : 1
372
+ - guarantor : 1
373
+ - relatnshp : 1
374
+ - purpose : 1
375
+ - sector : 1
376
+ - savings : 1",The sex is 0. The amnt req is 9000. The maturity is 30.0. The assets val is 5000. The dec profit is 320.0. The xperience is 9.0. The educatn is 4. The age is 38. The collateral is 9000. The locatn is 1. The guarantor is 1. The relatnshp is 1. The purpose is 1. The sector is 1. The savings is 1,"<table border=""1"" class=""dataframe"">
377
+ <thead>
378
+ <tr style=""text-align: right;"">
379
+ <th></th>
380
+ <th>sex</th>
381
+ <th>amnt req</th>
382
+ <th>maturity</th>
383
+ <th>assets val</th>
384
+ <th>dec profit</th>
385
+ <th>xperience</th>
386
+ <th>educatn</th>
387
+ <th>age</th>
388
+ <th>collateral</th>
389
+ <th>locatn</th>
390
+ <th>guarantor</th>
391
+ <th>relatnshp</th>
392
+ <th>purpose</th>
393
+ <th>sector</th>
394
+ <th>savings</th>
395
+ </tr>
396
+ </thead>
397
+ <tbody>
398
+ <tr>
399
+ <th>0</th>
400
+ <td>0</td>
401
+ <td>9000</td>
402
+ <td>30.0</td>
403
+ <td>5000</td>
404
+ <td>320.0</td>
405
+ <td>9.0</td>
406
+ <td>4</td>
407
+ <td>38</td>
408
+ <td>9000</td>
409
+ <td>1</td>
410
+ <td>1</td>
411
+ <td>1</td>
412
+ <td>1</td>
413
+ <td>1</td>
414
+ <td>1</td>
415
+ </tr>
416
+ </tbody>
417
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
418
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
419
+ 0 & 0 & 9000 & 30.000000 & 5000 & 320.000000 & 9.000000 & 4 & 38 & 9000 & 1 & 1 & 1 & 1 & 1 & 1 \\
420
+ \end{tabular}
421
+ ","{'age': 38, 'amnt req': 9000, 'assets val': 5000, 'collateral': 9000, 'dec profit': 320.0, 'educatn': 4, 'guarantor': 1, 'locatn': 1, 'maturity': 30.0, 'purpose': 1, 'relatnshp': 1, 'savings': 1, 'sector': 1, 'sex': 0, 'xperience': 9.0}",A 38-year-old female is applying for a loan of 9000 cedis. The applicant works in commerce sector and the purpose of the loan is not related to her business. The maturity period of the requested loan is 30.0 years. Her assets value is 5000 cedis and her declared profits (after tax) is 320.0 cedis. Her educational background is illiterate and the number of years that she has been in business is 9.0. She provided a guarantor and this is her first time requesting for a loan at the bank. She has non-mandatory savings with the bank. She resides or have her business close to the bank. The value of her collateral is 9000 cedis.
422
+ 7,1,12000,10000,1,30.0,10000,560.0,2.0,3,38,9000,1,1,1,0,4,0,No,"sex is 1, amnt req is 12000, maturity is 30.0, assets val is 10000, dec profit is 560.0, xperience is 2.0, educatn is 3, age is 38, collateral is 9000, locatn is 1, guarantor is 1, relatnshp is 1, purpose is 0, sector is 4, savings is 0","- sex : 1
423
+ - amnt req : 12000
424
+ - maturity : 30.0
425
+ - assets val : 10000
426
+ - dec profit : 560.0
427
+ - xperience : 2.0
428
+ - educatn : 3
429
+ - age : 38
430
+ - collateral : 9000
431
+ - locatn : 1
432
+ - guarantor : 1
433
+ - relatnshp : 1
434
+ - purpose : 0
435
+ - sector : 4
436
+ - savings : 0",The sex is 1. The amnt req is 12000. The maturity is 30.0. The assets val is 10000. The dec profit is 560.0. The xperience is 2.0. The educatn is 3. The age is 38. The collateral is 9000. The locatn is 1. The guarantor is 1. The relatnshp is 1. The purpose is 0. The sector is 4. The savings is 0,"<table border=""1"" class=""dataframe"">
437
+ <thead>
438
+ <tr style=""text-align: right;"">
439
+ <th></th>
440
+ <th>sex</th>
441
+ <th>amnt req</th>
442
+ <th>maturity</th>
443
+ <th>assets val</th>
444
+ <th>dec profit</th>
445
+ <th>xperience</th>
446
+ <th>educatn</th>
447
+ <th>age</th>
448
+ <th>collateral</th>
449
+ <th>locatn</th>
450
+ <th>guarantor</th>
451
+ <th>relatnshp</th>
452
+ <th>purpose</th>
453
+ <th>sector</th>
454
+ <th>savings</th>
455
+ </tr>
456
+ </thead>
457
+ <tbody>
458
+ <tr>
459
+ <th>0</th>
460
+ <td>1</td>
461
+ <td>12000</td>
462
+ <td>30.0</td>
463
+ <td>10000</td>
464
+ <td>560.0</td>
465
+ <td>2.0</td>
466
+ <td>3</td>
467
+ <td>38</td>
468
+ <td>9000</td>
469
+ <td>1</td>
470
+ <td>1</td>
471
+ <td>1</td>
472
+ <td>0</td>
473
+ <td>4</td>
474
+ <td>0</td>
475
+ </tr>
476
+ </tbody>
477
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
478
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
479
+ 0 & 1 & 12000 & 30.000000 & 10000 & 560.000000 & 2.000000 & 3 & 38 & 9000 & 1 & 1 & 1 & 0 & 4 & 0 \\
480
+ \end{tabular}
481
+ ","{'age': 38, 'amnt req': 12000, 'assets val': 10000, 'collateral': 9000, 'dec profit': 560.0, 'educatn': 3, 'guarantor': 1, 'locatn': 1, 'maturity': 30.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 4, 'sex': 1, 'xperience': 2.0}",A 38-year-old male is applying for a loan of 12000 cedis. The applicant works in agriculture sector and the purpose of the loan is related to his business. The maturity period of the requested loan is 30.0 years. His assets value is 10000 cedis and his declared profits (after tax) is 560.0 cedis. His educational background is primary and the number of years that he has been in business is 2.0. He provided a guarantor and this is his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He resides or have his business close to the bank. The value of his collateral is 9000 cedis.
482
+ 11,0,9000,8500,1,36.0,42000,2000.0,4.0,1,54,9000,0,1,1,1,3,1,No,"sex is 0, amnt req is 9000, maturity is 36.0, assets val is 42000, dec profit is 2000.0, xperience is 4.0, educatn is 1, age is 54, collateral is 9000, locatn is 0, guarantor is 1, relatnshp is 1, purpose is 1, sector is 3, savings is 1","- sex : 0
483
+ - amnt req : 9000
484
+ - maturity : 36.0
485
+ - assets val : 42000
486
+ - dec profit : 2000.0
487
+ - xperience : 4.0
488
+ - educatn : 1
489
+ - age : 54
490
+ - collateral : 9000
491
+ - locatn : 0
492
+ - guarantor : 1
493
+ - relatnshp : 1
494
+ - purpose : 1
495
+ - sector : 3
496
+ - savings : 1",The sex is 0. The amnt req is 9000. The maturity is 36.0. The assets val is 42000. The dec profit is 2000.0. The xperience is 4.0. The educatn is 1. The age is 54. The collateral is 9000. The locatn is 0. The guarantor is 1. The relatnshp is 1. The purpose is 1. The sector is 3. The savings is 1,"<table border=""1"" class=""dataframe"">
497
+ <thead>
498
+ <tr style=""text-align: right;"">
499
+ <th></th>
500
+ <th>sex</th>
501
+ <th>amnt req</th>
502
+ <th>maturity</th>
503
+ <th>assets val</th>
504
+ <th>dec profit</th>
505
+ <th>xperience</th>
506
+ <th>educatn</th>
507
+ <th>age</th>
508
+ <th>collateral</th>
509
+ <th>locatn</th>
510
+ <th>guarantor</th>
511
+ <th>relatnshp</th>
512
+ <th>purpose</th>
513
+ <th>sector</th>
514
+ <th>savings</th>
515
+ </tr>
516
+ </thead>
517
+ <tbody>
518
+ <tr>
519
+ <th>0</th>
520
+ <td>0</td>
521
+ <td>9000</td>
522
+ <td>36.0</td>
523
+ <td>42000</td>
524
+ <td>2000.0</td>
525
+ <td>4.0</td>
526
+ <td>1</td>
527
+ <td>54</td>
528
+ <td>9000</td>
529
+ <td>0</td>
530
+ <td>1</td>
531
+ <td>1</td>
532
+ <td>1</td>
533
+ <td>3</td>
534
+ <td>1</td>
535
+ </tr>
536
+ </tbody>
537
+ </table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
538
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
539
+ 0 & 0 & 9000 & 36.000000 & 42000 & 2000.000000 & 4.000000 & 1 & 54 & 9000 & 0 & 1 & 1 & 1 & 3 & 1 \\
540
+ \end{tabular}
541
+ ","{'age': 54, 'amnt req': 9000, 'assets val': 42000, 'collateral': 9000, 'dec profit': 2000.0, 'educatn': 1, 'guarantor': 1, 'locatn': 0, 'maturity': 36.0, 'purpose': 1, 'relatnshp': 1, 'savings': 1, 'sector': 3, 'sex': 0, 'xperience': 4.0}",A 54-year-old female is applying for a loan of 9000 cedis. The applicant works in manufacturing sector and the purpose of the loan is not related to her business. The maturity period of the requested loan is 36.0 years. Her assets value is 42000 cedis and her declared profits (after tax) is 2000.0 cedis. Her educational background is tertiary and the number of years that she has been in business is 4.0. She provided a guarantor and this is her first time requesting for a loan at the bank. She has non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 9000 cedis.
542
+ 8,1,9000,6000,1,,9000,1200.0,8.0,3,40,7000,1,1,0,1,4,0,No,"sex is 1, amnt req is 9000, maturity is None, assets val is 9000, dec profit is 1200.0, xperience is 8.0, educatn is 3, age is 40, collateral is 7000, locatn is 1, guarantor is 1, relatnshp is 0, purpose is 1, sector is 4, savings is 0","- sex : 1
543
+ - amnt req : 9000
544
+ - maturity : None
545
+ - assets val : 9000
546
+ - dec profit : 1200.0
547
+ - xperience : 8.0
548
+ - educatn : 3
549
+ - age : 40
550
+ - collateral : 7000
551
+ - locatn : 1
552
+ - guarantor : 1
553
+ - relatnshp : 0
554
+ - purpose : 1
555
+ - sector : 4
556
+ - savings : 0",The sex is 1. The amnt req is 9000. The maturity is None. The assets val is 9000. The dec profit is 1200.0. The xperience is 8.0. The educatn is 3. The age is 40. The collateral is 7000. The locatn is 1. The guarantor is 1. The relatnshp is 0. The purpose is 1. The sector is 4. The savings is 0,"<table border=""1"" class=""dataframe"">
557
+ <thead>
558
+ <tr style=""text-align: right;"">
559
+ <th></th>
560
+ <th>sex</th>
561
+ <th>amnt req</th>
562
+ <th>maturity</th>
563
+ <th>assets val</th>
564
+ <th>dec profit</th>
565
+ <th>xperience</th>
566
+ <th>educatn</th>
567
+ <th>age</th>
568
+ <th>collateral</th>
569
+ <th>locatn</th>
570
+ <th>guarantor</th>
571
+ <th>relatnshp</th>
572
+ <th>purpose</th>
573
+ <th>sector</th>
574
+ <th>savings</th>
575
+ </tr>
576
+ </thead>
577
+ <tbody>
578
+ <tr>
579
+ <th>0</th>
580
+ <td>1</td>
581
+ <td>9000</td>
582
+ <td>None</td>
583
+ <td>9000</td>
584
+ <td>1200.0</td>
585
+ <td>8.0</td>
586
+ <td>3</td>
587
+ <td>40</td>
588
+ <td>7000</td>
589
+ <td>1</td>
590
+ <td>1</td>
591
+ <td>0</td>
592
+ <td>1</td>
593
+ <td>4</td>
594
+ <td>0</td>
595
+ </tr>
596
+ </tbody>
597
+ </table>","\begin{tabular}{lrrlrrrrrrrrrrrr}
598
+ & sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
599
+ 0 & 1 & 9000 & None & 9000 & 1200.000000 & 8.000000 & 3 & 40 & 7000 & 1 & 1 & 0 & 1 & 4 & 0 \\
600
+ \end{tabular}
601
+ ","{'age': 40, 'amnt req': 9000, 'assets val': 9000, 'collateral': 7000, 'dec profit': 1200.0, 'educatn': 3, 'guarantor': 1, 'locatn': 1, 'maturity': None, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 4, 'sex': 1, 'xperience': 8.0}",A 40-year-old male is applying for a loan of 9000 cedis. The applicant works in agriculture sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is None years. His assets value is 9000 cedis and his declared profits (after tax) is 1200.0 cedis. His educational background is primary and the number of years that he has been in business is 8.0. He provided a guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He resides or have his business close to the bank. The value of his collateral is 7000 cedis.
new_data/ghana-test.csv ADDED
The diff for this file is too large to render. See raw diff
 
new_data/ghana-train.csv ADDED
The diff for this file is too large to render. See raw diff
 
new_data/loan_pred-fewshot-2.csv ADDED
@@ -0,0 +1,97 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Unnamed: 0,Gender,Loan_ID,Gender.1,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_Status,great,list,text,html,latex,json,LIFT
2
+ 0,Male,LP001273,Male,Yes,0,Graduate,No,6000,2250.0,265.0,360.0,,Semiurban,N,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 6000, CoapplicantIncome is 2250.0, LoanAmount is 265.0, Loan_Amount_Term is 360.0, Credit_History is None, Property_Area is Semiurban","- Gender : Male
3
+ - Married : Yes
4
+ - Dependents : 0
5
+ - Education : Graduate
6
+ - Self_Employed : No
7
+ - ApplicantIncome : 6000
8
+ - CoapplicantIncome : 2250.0
9
+ - LoanAmount : 265.0
10
+ - Loan_Amount_Term : 360.0
11
+ - Credit_History : None
12
+ - Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 6000. The CoapplicantIncome is 2250.0. The LoanAmount is 265.0. The Loan_Amount_Term is 360.0. The Credit_History is None. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
13
+ <thead>
14
+ <tr style=""text-align: right;"">
15
+ <th></th>
16
+ <th>Gender</th>
17
+ <th>Married</th>
18
+ <th>Dependents</th>
19
+ <th>Education</th>
20
+ <th>Self_Employed</th>
21
+ <th>ApplicantIncome</th>
22
+ <th>CoapplicantIncome</th>
23
+ <th>LoanAmount</th>
24
+ <th>Loan_Amount_Term</th>
25
+ <th>Credit_History</th>
26
+ <th>Property_Area</th>
27
+ </tr>
28
+ </thead>
29
+ <tbody>
30
+ <tr>
31
+ <th>0</th>
32
+ <td>Male</td>
33
+ <td>Yes</td>
34
+ <td>0</td>
35
+ <td>Graduate</td>
36
+ <td>No</td>
37
+ <td>6000</td>
38
+ <td>2250.0</td>
39
+ <td>265.0</td>
40
+ <td>360.0</td>
41
+ <td>None</td>
42
+ <td>Semiurban</td>
43
+ </tr>
44
+ </tbody>
45
+ </table>","\begin{tabular}{llllllrrrrll}
46
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
47
+ 0 & Male & Yes & 0 & Graduate & No & 6000 & 2250.000000 & 265.000000 & 360.000000 & None & Semiurban \\
48
+ \end{tabular}
49
+ ","{'ApplicantIncome': 6000, 'CoapplicantIncome': 2250.0, 'Credit_History': None, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 265.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 265.0 dollars for 30.0 months. He has unknown credit history. He is a graduate and is not self employed. He earns 6000 dollars and his co-applicant earns 2250.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
50
+ 8,Female,LP001639,Female,Yes,0,Graduate,No,3625,0.0,108.0,360.0,1.0,Semiurban,Y,"Gender is Female, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 3625, CoapplicantIncome is 0.0, LoanAmount is 108.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Female
51
+ - Married : Yes
52
+ - Dependents : 0
53
+ - Education : Graduate
54
+ - Self_Employed : No
55
+ - ApplicantIncome : 3625
56
+ - CoapplicantIncome : 0.0
57
+ - LoanAmount : 108.0
58
+ - Loan_Amount_Term : 360.0
59
+ - Credit_History : 1.0
60
+ - Property_Area : Semiurban",The Gender is Female. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 3625. The CoapplicantIncome is 0.0. The LoanAmount is 108.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
61
+ <thead>
62
+ <tr style=""text-align: right;"">
63
+ <th></th>
64
+ <th>Gender</th>
65
+ <th>Married</th>
66
+ <th>Dependents</th>
67
+ <th>Education</th>
68
+ <th>Self_Employed</th>
69
+ <th>ApplicantIncome</th>
70
+ <th>CoapplicantIncome</th>
71
+ <th>LoanAmount</th>
72
+ <th>Loan_Amount_Term</th>
73
+ <th>Credit_History</th>
74
+ <th>Property_Area</th>
75
+ </tr>
76
+ </thead>
77
+ <tbody>
78
+ <tr>
79
+ <th>0</th>
80
+ <td>Female</td>
81
+ <td>Yes</td>
82
+ <td>0</td>
83
+ <td>Graduate</td>
84
+ <td>No</td>
85
+ <td>3625</td>
86
+ <td>0.0</td>
87
+ <td>108.0</td>
88
+ <td>360.0</td>
89
+ <td>1.0</td>
90
+ <td>Semiurban</td>
91
+ </tr>
92
+ </tbody>
93
+ </table>","\begin{tabular}{llllllrrrrrl}
94
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
95
+ 0 & Female & Yes & 0 & Graduate & No & 3625 & 0.000000 & 108.000000 & 360.000000 & 1.000000 & Semiurban \\
96
+ \end{tabular}
97
+ ","{'ApplicantIncome': 3625, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Female', 'LoanAmount': 108.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married female individual is applying for a loan of 108.0 dollars for 30.0 months. She has a credit history. She is a graduate and is not self employed. She earns 3625 dollars. She has no person that she is liable to provide maintenance for. She lives in semiurban area.
new_data/loan_pred-fewshot-4.csv ADDED
@@ -0,0 +1,193 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Unnamed: 0,Gender,Loan_ID,Gender.1,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_Status,great,list,text,html,latex,json,LIFT
2
+ 0,Male,LP001273,Male,Yes,0,Graduate,No,6000,2250.0,265.0,360.0,,Semiurban,N,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 6000, CoapplicantIncome is 2250.0, LoanAmount is 265.0, Loan_Amount_Term is 360.0, Credit_History is None, Property_Area is Semiurban","- Gender : Male
3
+ - Married : Yes
4
+ - Dependents : 0
5
+ - Education : Graduate
6
+ - Self_Employed : No
7
+ - ApplicantIncome : 6000
8
+ - CoapplicantIncome : 2250.0
9
+ - LoanAmount : 265.0
10
+ - Loan_Amount_Term : 360.0
11
+ - Credit_History : None
12
+ - Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 6000. The CoapplicantIncome is 2250.0. The LoanAmount is 265.0. The Loan_Amount_Term is 360.0. The Credit_History is None. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
13
+ <thead>
14
+ <tr style=""text-align: right;"">
15
+ <th></th>
16
+ <th>Gender</th>
17
+ <th>Married</th>
18
+ <th>Dependents</th>
19
+ <th>Education</th>
20
+ <th>Self_Employed</th>
21
+ <th>ApplicantIncome</th>
22
+ <th>CoapplicantIncome</th>
23
+ <th>LoanAmount</th>
24
+ <th>Loan_Amount_Term</th>
25
+ <th>Credit_History</th>
26
+ <th>Property_Area</th>
27
+ </tr>
28
+ </thead>
29
+ <tbody>
30
+ <tr>
31
+ <th>0</th>
32
+ <td>Male</td>
33
+ <td>Yes</td>
34
+ <td>0</td>
35
+ <td>Graduate</td>
36
+ <td>No</td>
37
+ <td>6000</td>
38
+ <td>2250.0</td>
39
+ <td>265.0</td>
40
+ <td>360.0</td>
41
+ <td>None</td>
42
+ <td>Semiurban</td>
43
+ </tr>
44
+ </tbody>
45
+ </table>","\begin{tabular}{llllllrrrrll}
46
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
47
+ 0 & Male & Yes & 0 & Graduate & No & 6000 & 2250.000000 & 265.000000 & 360.000000 & None & Semiurban \\
48
+ \end{tabular}
49
+ ","{'ApplicantIncome': 6000, 'CoapplicantIncome': 2250.0, 'Credit_History': None, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 265.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 265.0 dollars for 30.0 months. He has unknown credit history. He is a graduate and is not self employed. He earns 6000 dollars and his co-applicant earns 2250.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
50
+ 8,Female,LP001639,Female,Yes,0,Graduate,No,3625,0.0,108.0,360.0,1.0,Semiurban,Y,"Gender is Female, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 3625, CoapplicantIncome is 0.0, LoanAmount is 108.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Female
51
+ - Married : Yes
52
+ - Dependents : 0
53
+ - Education : Graduate
54
+ - Self_Employed : No
55
+ - ApplicantIncome : 3625
56
+ - CoapplicantIncome : 0.0
57
+ - LoanAmount : 108.0
58
+ - Loan_Amount_Term : 360.0
59
+ - Credit_History : 1.0
60
+ - Property_Area : Semiurban",The Gender is Female. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 3625. The CoapplicantIncome is 0.0. The LoanAmount is 108.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
61
+ <thead>
62
+ <tr style=""text-align: right;"">
63
+ <th></th>
64
+ <th>Gender</th>
65
+ <th>Married</th>
66
+ <th>Dependents</th>
67
+ <th>Education</th>
68
+ <th>Self_Employed</th>
69
+ <th>ApplicantIncome</th>
70
+ <th>CoapplicantIncome</th>
71
+ <th>LoanAmount</th>
72
+ <th>Loan_Amount_Term</th>
73
+ <th>Credit_History</th>
74
+ <th>Property_Area</th>
75
+ </tr>
76
+ </thead>
77
+ <tbody>
78
+ <tr>
79
+ <th>0</th>
80
+ <td>Female</td>
81
+ <td>Yes</td>
82
+ <td>0</td>
83
+ <td>Graduate</td>
84
+ <td>No</td>
85
+ <td>3625</td>
86
+ <td>0.0</td>
87
+ <td>108.0</td>
88
+ <td>360.0</td>
89
+ <td>1.0</td>
90
+ <td>Semiurban</td>
91
+ </tr>
92
+ </tbody>
93
+ </table>","\begin{tabular}{llllllrrrrrl}
94
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
95
+ 0 & Female & Yes & 0 & Graduate & No & 3625 & 0.000000 & 108.000000 & 360.000000 & 1.000000 & Semiurban \\
96
+ \end{tabular}
97
+ ","{'ApplicantIncome': 3625, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Female', 'LoanAmount': 108.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married female individual is applying for a loan of 108.0 dollars for 30.0 months. She has a credit history. She is a graduate and is not self employed. She earns 3625 dollars. She has no person that she is liable to provide maintenance for. She lives in semiurban area.
98
+ 1,Male,LP001316,Male,Yes,0,Graduate,No,2958,2900.0,131.0,360.0,1.0,Semiurban,Y,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 2958, CoapplicantIncome is 2900.0, LoanAmount is 131.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Male
99
+ - Married : Yes
100
+ - Dependents : 0
101
+ - Education : Graduate
102
+ - Self_Employed : No
103
+ - ApplicantIncome : 2958
104
+ - CoapplicantIncome : 2900.0
105
+ - LoanAmount : 131.0
106
+ - Loan_Amount_Term : 360.0
107
+ - Credit_History : 1.0
108
+ - Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 2958. The CoapplicantIncome is 2900.0. The LoanAmount is 131.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
109
+ <thead>
110
+ <tr style=""text-align: right;"">
111
+ <th></th>
112
+ <th>Gender</th>
113
+ <th>Married</th>
114
+ <th>Dependents</th>
115
+ <th>Education</th>
116
+ <th>Self_Employed</th>
117
+ <th>ApplicantIncome</th>
118
+ <th>CoapplicantIncome</th>
119
+ <th>LoanAmount</th>
120
+ <th>Loan_Amount_Term</th>
121
+ <th>Credit_History</th>
122
+ <th>Property_Area</th>
123
+ </tr>
124
+ </thead>
125
+ <tbody>
126
+ <tr>
127
+ <th>0</th>
128
+ <td>Male</td>
129
+ <td>Yes</td>
130
+ <td>0</td>
131
+ <td>Graduate</td>
132
+ <td>No</td>
133
+ <td>2958</td>
134
+ <td>2900.0</td>
135
+ <td>131.0</td>
136
+ <td>360.0</td>
137
+ <td>1.0</td>
138
+ <td>Semiurban</td>
139
+ </tr>
140
+ </tbody>
141
+ </table>","\begin{tabular}{llllllrrrrrl}
142
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
143
+ 0 & Male & Yes & 0 & Graduate & No & 2958 & 2900.000000 & 131.000000 & 360.000000 & 1.000000 & Semiurban \\
144
+ \end{tabular}
145
+ ","{'ApplicantIncome': 2958, 'CoapplicantIncome': 2900.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 131.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 131.0 dollars for 30.0 months. He has a credit history. He is a graduate and is not self employed. He earns 2958 dollars and his co-applicant earns 2900.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
146
+ 19,Female,LP002367,Female,No,1,Not Graduate,No,4606,0.0,81.0,360.0,1.0,Rural,N,"Gender is Female, Married is No, Dependents is 1, Education is Not Graduate, Self_Employed is No, ApplicantIncome is 4606, CoapplicantIncome is 0.0, LoanAmount is 81.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Rural","- Gender : Female
147
+ - Married : No
148
+ - Dependents : 1
149
+ - Education : Not Graduate
150
+ - Self_Employed : No
151
+ - ApplicantIncome : 4606
152
+ - CoapplicantIncome : 0.0
153
+ - LoanAmount : 81.0
154
+ - Loan_Amount_Term : 360.0
155
+ - Credit_History : 1.0
156
+ - Property_Area : Rural",The Gender is Female. The Married is No. The Dependents is 1. The Education is Not Graduate. The Self_Employed is No. The ApplicantIncome is 4606. The CoapplicantIncome is 0.0. The LoanAmount is 81.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Rural,"<table border=""1"" class=""dataframe"">
157
+ <thead>
158
+ <tr style=""text-align: right;"">
159
+ <th></th>
160
+ <th>Gender</th>
161
+ <th>Married</th>
162
+ <th>Dependents</th>
163
+ <th>Education</th>
164
+ <th>Self_Employed</th>
165
+ <th>ApplicantIncome</th>
166
+ <th>CoapplicantIncome</th>
167
+ <th>LoanAmount</th>
168
+ <th>Loan_Amount_Term</th>
169
+ <th>Credit_History</th>
170
+ <th>Property_Area</th>
171
+ </tr>
172
+ </thead>
173
+ <tbody>
174
+ <tr>
175
+ <th>0</th>
176
+ <td>Female</td>
177
+ <td>No</td>
178
+ <td>1</td>
179
+ <td>Not Graduate</td>
180
+ <td>No</td>
181
+ <td>4606</td>
182
+ <td>0.0</td>
183
+ <td>81.0</td>
184
+ <td>360.0</td>
185
+ <td>1.0</td>
186
+ <td>Rural</td>
187
+ </tr>
188
+ </tbody>
189
+ </table>","\begin{tabular}{llllllrrrrrl}
190
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
191
+ 0 & Female & No & 1 & Not Graduate & No & 4606 & 0.000000 & 81.000000 & 360.000000 & 1.000000 & Rural \\
192
+ \end{tabular}
193
+ ","{'ApplicantIncome': 4606, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '1', 'Education': 'Not Graduate', 'Gender': 'Female', 'LoanAmount': 81.0, 'Loan_Amount_Term': 360.0, 'Married': 'No', 'Property_Area': 'Rural', 'Self_Employed': 'No'}",A unmarried female individual is applying for a loan of 81.0 dollars for 30.0 months. She has a credit history. She is not a graduate and is not self employed. She earns 4606 dollars. She has 1 person that she is liable to provide maintenance for. She lives in rural area.
new_data/loan_pred-fewshot-6.csv ADDED
@@ -0,0 +1,289 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Unnamed: 0,Gender,Loan_ID,Gender.1,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_Status,great,list,text,html,latex,json,LIFT
2
+ 0,Male,LP001273,Male,Yes,0,Graduate,No,6000,2250.0,265.0,360.0,,Semiurban,N,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 6000, CoapplicantIncome is 2250.0, LoanAmount is 265.0, Loan_Amount_Term is 360.0, Credit_History is None, Property_Area is Semiurban","- Gender : Male
3
+ - Married : Yes
4
+ - Dependents : 0
5
+ - Education : Graduate
6
+ - Self_Employed : No
7
+ - ApplicantIncome : 6000
8
+ - CoapplicantIncome : 2250.0
9
+ - LoanAmount : 265.0
10
+ - Loan_Amount_Term : 360.0
11
+ - Credit_History : None
12
+ - Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 6000. The CoapplicantIncome is 2250.0. The LoanAmount is 265.0. The Loan_Amount_Term is 360.0. The Credit_History is None. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
13
+ <thead>
14
+ <tr style=""text-align: right;"">
15
+ <th></th>
16
+ <th>Gender</th>
17
+ <th>Married</th>
18
+ <th>Dependents</th>
19
+ <th>Education</th>
20
+ <th>Self_Employed</th>
21
+ <th>ApplicantIncome</th>
22
+ <th>CoapplicantIncome</th>
23
+ <th>LoanAmount</th>
24
+ <th>Loan_Amount_Term</th>
25
+ <th>Credit_History</th>
26
+ <th>Property_Area</th>
27
+ </tr>
28
+ </thead>
29
+ <tbody>
30
+ <tr>
31
+ <th>0</th>
32
+ <td>Male</td>
33
+ <td>Yes</td>
34
+ <td>0</td>
35
+ <td>Graduate</td>
36
+ <td>No</td>
37
+ <td>6000</td>
38
+ <td>2250.0</td>
39
+ <td>265.0</td>
40
+ <td>360.0</td>
41
+ <td>None</td>
42
+ <td>Semiurban</td>
43
+ </tr>
44
+ </tbody>
45
+ </table>","\begin{tabular}{llllllrrrrll}
46
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
47
+ 0 & Male & Yes & 0 & Graduate & No & 6000 & 2250.000000 & 265.000000 & 360.000000 & None & Semiurban \\
48
+ \end{tabular}
49
+ ","{'ApplicantIncome': 6000, 'CoapplicantIncome': 2250.0, 'Credit_History': None, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 265.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 265.0 dollars for 30.0 months. He has unknown credit history. He is a graduate and is not self employed. He earns 6000 dollars and his co-applicant earns 2250.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
50
+ 8,Female,LP001639,Female,Yes,0,Graduate,No,3625,0.0,108.0,360.0,1.0,Semiurban,Y,"Gender is Female, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 3625, CoapplicantIncome is 0.0, LoanAmount is 108.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Female
51
+ - Married : Yes
52
+ - Dependents : 0
53
+ - Education : Graduate
54
+ - Self_Employed : No
55
+ - ApplicantIncome : 3625
56
+ - CoapplicantIncome : 0.0
57
+ - LoanAmount : 108.0
58
+ - Loan_Amount_Term : 360.0
59
+ - Credit_History : 1.0
60
+ - Property_Area : Semiurban",The Gender is Female. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 3625. The CoapplicantIncome is 0.0. The LoanAmount is 108.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
61
+ <thead>
62
+ <tr style=""text-align: right;"">
63
+ <th></th>
64
+ <th>Gender</th>
65
+ <th>Married</th>
66
+ <th>Dependents</th>
67
+ <th>Education</th>
68
+ <th>Self_Employed</th>
69
+ <th>ApplicantIncome</th>
70
+ <th>CoapplicantIncome</th>
71
+ <th>LoanAmount</th>
72
+ <th>Loan_Amount_Term</th>
73
+ <th>Credit_History</th>
74
+ <th>Property_Area</th>
75
+ </tr>
76
+ </thead>
77
+ <tbody>
78
+ <tr>
79
+ <th>0</th>
80
+ <td>Female</td>
81
+ <td>Yes</td>
82
+ <td>0</td>
83
+ <td>Graduate</td>
84
+ <td>No</td>
85
+ <td>3625</td>
86
+ <td>0.0</td>
87
+ <td>108.0</td>
88
+ <td>360.0</td>
89
+ <td>1.0</td>
90
+ <td>Semiurban</td>
91
+ </tr>
92
+ </tbody>
93
+ </table>","\begin{tabular}{llllllrrrrrl}
94
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
95
+ 0 & Female & Yes & 0 & Graduate & No & 3625 & 0.000000 & 108.000000 & 360.000000 & 1.000000 & Semiurban \\
96
+ \end{tabular}
97
+ ","{'ApplicantIncome': 3625, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Female', 'LoanAmount': 108.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married female individual is applying for a loan of 108.0 dollars for 30.0 months. She has a credit history. She is a graduate and is not self employed. She earns 3625 dollars. She has no person that she is liable to provide maintenance for. She lives in semiurban area.
98
+ 1,Male,LP001316,Male,Yes,0,Graduate,No,2958,2900.0,131.0,360.0,1.0,Semiurban,Y,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 2958, CoapplicantIncome is 2900.0, LoanAmount is 131.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Male
99
+ - Married : Yes
100
+ - Dependents : 0
101
+ - Education : Graduate
102
+ - Self_Employed : No
103
+ - ApplicantIncome : 2958
104
+ - CoapplicantIncome : 2900.0
105
+ - LoanAmount : 131.0
106
+ - Loan_Amount_Term : 360.0
107
+ - Credit_History : 1.0
108
+ - Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 2958. The CoapplicantIncome is 2900.0. The LoanAmount is 131.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
109
+ <thead>
110
+ <tr style=""text-align: right;"">
111
+ <th></th>
112
+ <th>Gender</th>
113
+ <th>Married</th>
114
+ <th>Dependents</th>
115
+ <th>Education</th>
116
+ <th>Self_Employed</th>
117
+ <th>ApplicantIncome</th>
118
+ <th>CoapplicantIncome</th>
119
+ <th>LoanAmount</th>
120
+ <th>Loan_Amount_Term</th>
121
+ <th>Credit_History</th>
122
+ <th>Property_Area</th>
123
+ </tr>
124
+ </thead>
125
+ <tbody>
126
+ <tr>
127
+ <th>0</th>
128
+ <td>Male</td>
129
+ <td>Yes</td>
130
+ <td>0</td>
131
+ <td>Graduate</td>
132
+ <td>No</td>
133
+ <td>2958</td>
134
+ <td>2900.0</td>
135
+ <td>131.0</td>
136
+ <td>360.0</td>
137
+ <td>1.0</td>
138
+ <td>Semiurban</td>
139
+ </tr>
140
+ </tbody>
141
+ </table>","\begin{tabular}{llllllrrrrrl}
142
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
143
+ 0 & Male & Yes & 0 & Graduate & No & 2958 & 2900.000000 & 131.000000 & 360.000000 & 1.000000 & Semiurban \\
144
+ \end{tabular}
145
+ ","{'ApplicantIncome': 2958, 'CoapplicantIncome': 2900.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 131.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 131.0 dollars for 30.0 months. He has a credit history. He is a graduate and is not self employed. He earns 2958 dollars and his co-applicant earns 2900.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
146
+ 19,Female,LP002367,Female,No,1,Not Graduate,No,4606,0.0,81.0,360.0,1.0,Rural,N,"Gender is Female, Married is No, Dependents is 1, Education is Not Graduate, Self_Employed is No, ApplicantIncome is 4606, CoapplicantIncome is 0.0, LoanAmount is 81.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Rural","- Gender : Female
147
+ - Married : No
148
+ - Dependents : 1
149
+ - Education : Not Graduate
150
+ - Self_Employed : No
151
+ - ApplicantIncome : 4606
152
+ - CoapplicantIncome : 0.0
153
+ - LoanAmount : 81.0
154
+ - Loan_Amount_Term : 360.0
155
+ - Credit_History : 1.0
156
+ - Property_Area : Rural",The Gender is Female. The Married is No. The Dependents is 1. The Education is Not Graduate. The Self_Employed is No. The ApplicantIncome is 4606. The CoapplicantIncome is 0.0. The LoanAmount is 81.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Rural,"<table border=""1"" class=""dataframe"">
157
+ <thead>
158
+ <tr style=""text-align: right;"">
159
+ <th></th>
160
+ <th>Gender</th>
161
+ <th>Married</th>
162
+ <th>Dependents</th>
163
+ <th>Education</th>
164
+ <th>Self_Employed</th>
165
+ <th>ApplicantIncome</th>
166
+ <th>CoapplicantIncome</th>
167
+ <th>LoanAmount</th>
168
+ <th>Loan_Amount_Term</th>
169
+ <th>Credit_History</th>
170
+ <th>Property_Area</th>
171
+ </tr>
172
+ </thead>
173
+ <tbody>
174
+ <tr>
175
+ <th>0</th>
176
+ <td>Female</td>
177
+ <td>No</td>
178
+ <td>1</td>
179
+ <td>Not Graduate</td>
180
+ <td>No</td>
181
+ <td>4606</td>
182
+ <td>0.0</td>
183
+ <td>81.0</td>
184
+ <td>360.0</td>
185
+ <td>1.0</td>
186
+ <td>Rural</td>
187
+ </tr>
188
+ </tbody>
189
+ </table>","\begin{tabular}{llllllrrrrrl}
190
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
191
+ 0 & Female & No & 1 & Not Graduate & No & 4606 & 0.000000 & 81.000000 & 360.000000 & 1.000000 & Rural \\
192
+ \end{tabular}
193
+ ","{'ApplicantIncome': 4606, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '1', 'Education': 'Not Graduate', 'Gender': 'Female', 'LoanAmount': 81.0, 'Loan_Amount_Term': 360.0, 'Married': 'No', 'Property_Area': 'Rural', 'Self_Employed': 'No'}",A unmarried female individual is applying for a loan of 81.0 dollars for 30.0 months. She has a credit history. She is not a graduate and is not self employed. She earns 4606 dollars. She has 1 person that she is liable to provide maintenance for. She lives in rural area.
194
+ 2,Male,LP001758,Male,Yes,2,Graduate,No,6250,1695.0,210.0,360.0,1.0,Semiurban,Y,"Gender is Male, Married is Yes, Dependents is 2, Education is Graduate, Self_Employed is No, ApplicantIncome is 6250, CoapplicantIncome is 1695.0, LoanAmount is 210.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Male
195
+ - Married : Yes
196
+ - Dependents : 2
197
+ - Education : Graduate
198
+ - Self_Employed : No
199
+ - ApplicantIncome : 6250
200
+ - CoapplicantIncome : 1695.0
201
+ - LoanAmount : 210.0
202
+ - Loan_Amount_Term : 360.0
203
+ - Credit_History : 1.0
204
+ - Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 2. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 6250. The CoapplicantIncome is 1695.0. The LoanAmount is 210.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
205
+ <thead>
206
+ <tr style=""text-align: right;"">
207
+ <th></th>
208
+ <th>Gender</th>
209
+ <th>Married</th>
210
+ <th>Dependents</th>
211
+ <th>Education</th>
212
+ <th>Self_Employed</th>
213
+ <th>ApplicantIncome</th>
214
+ <th>CoapplicantIncome</th>
215
+ <th>LoanAmount</th>
216
+ <th>Loan_Amount_Term</th>
217
+ <th>Credit_History</th>
218
+ <th>Property_Area</th>
219
+ </tr>
220
+ </thead>
221
+ <tbody>
222
+ <tr>
223
+ <th>0</th>
224
+ <td>Male</td>
225
+ <td>Yes</td>
226
+ <td>2</td>
227
+ <td>Graduate</td>
228
+ <td>No</td>
229
+ <td>6250</td>
230
+ <td>1695.0</td>
231
+ <td>210.0</td>
232
+ <td>360.0</td>
233
+ <td>1.0</td>
234
+ <td>Semiurban</td>
235
+ </tr>
236
+ </tbody>
237
+ </table>","\begin{tabular}{llllllrrrrrl}
238
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
239
+ 0 & Male & Yes & 2 & Graduate & No & 6250 & 1695.000000 & 210.000000 & 360.000000 & 1.000000 & Semiurban \\
240
+ \end{tabular}
241
+ ","{'ApplicantIncome': 6250, 'CoapplicantIncome': 1695.0, 'Credit_History': 1.0, 'Dependents': '2', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 210.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 210.0 dollars for 30.0 months. He has a credit history. He is a graduate and is not self employed. He earns 6250 dollars and his co-applicant earns 1695.0 dollars. He has 2 people that he is liable to provide maintenance for. He lives in semiurban area.
242
+ 20,Female,LP002949,Female,No,3+,Graduate,,416,41667.0,350.0,180.0,,Urban,N,"Gender is Female, Married is No, Dependents is 3+, Education is Graduate, Self_Employed is None, ApplicantIncome is 416, CoapplicantIncome is 41667.0, LoanAmount is 350.0, Loan_Amount_Term is 180.0, Credit_History is None, Property_Area is Urban","- Gender : Female
243
+ - Married : No
244
+ - Dependents : 3+
245
+ - Education : Graduate
246
+ - Self_Employed : None
247
+ - ApplicantIncome : 416
248
+ - CoapplicantIncome : 41667.0
249
+ - LoanAmount : 350.0
250
+ - Loan_Amount_Term : 180.0
251
+ - Credit_History : None
252
+ - Property_Area : Urban",The Gender is Female. The Married is No. The Dependents is 3+. The Education is Graduate. The Self_Employed is None. The ApplicantIncome is 416. The CoapplicantIncome is 41667.0. The LoanAmount is 350.0. The Loan_Amount_Term is 180.0. The Credit_History is None. The Property_Area is Urban,"<table border=""1"" class=""dataframe"">
253
+ <thead>
254
+ <tr style=""text-align: right;"">
255
+ <th></th>
256
+ <th>Gender</th>
257
+ <th>Married</th>
258
+ <th>Dependents</th>
259
+ <th>Education</th>
260
+ <th>Self_Employed</th>
261
+ <th>ApplicantIncome</th>
262
+ <th>CoapplicantIncome</th>
263
+ <th>LoanAmount</th>
264
+ <th>Loan_Amount_Term</th>
265
+ <th>Credit_History</th>
266
+ <th>Property_Area</th>
267
+ </tr>
268
+ </thead>
269
+ <tbody>
270
+ <tr>
271
+ <th>0</th>
272
+ <td>Female</td>
273
+ <td>No</td>
274
+ <td>3+</td>
275
+ <td>Graduate</td>
276
+ <td>None</td>
277
+ <td>416</td>
278
+ <td>41667.0</td>
279
+ <td>350.0</td>
280
+ <td>180.0</td>
281
+ <td>None</td>
282
+ <td>Urban</td>
283
+ </tr>
284
+ </tbody>
285
+ </table>","\begin{tabular}{llllllrrrrll}
286
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
287
+ 0 & Female & No & 3+ & Graduate & None & 416 & 41667.000000 & 350.000000 & 180.000000 & None & Urban \\
288
+ \end{tabular}
289
+ ","{'ApplicantIncome': 416, 'CoapplicantIncome': 41667.0, 'Credit_History': None, 'Dependents': '3+', 'Education': 'Graduate', 'Gender': 'Female', 'LoanAmount': 350.0, 'Loan_Amount_Term': 180.0, 'Married': 'No', 'Property_Area': 'Urban', 'Self_Employed': None}",A unmarried female individual is applying for a loan of 350.0 dollars for 15.0 months. She has unknown credit history. She is a graduate and has unknown self employment status. She earns 416 dollars and her co-applicant earns 41667.0 dollars. She has 3+ people that she is liable to provide maintenance for. She lives in urban area.
new_data/loan_pred-fewshot-8.csv ADDED
@@ -0,0 +1,385 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Unnamed: 0,Gender,Loan_ID,Gender.1,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_Status,great,list,text,html,latex,json,LIFT
2
+ 0,Male,LP001273,Male,Yes,0,Graduate,No,6000,2250.0,265.0,360.0,,Semiurban,N,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 6000, CoapplicantIncome is 2250.0, LoanAmount is 265.0, Loan_Amount_Term is 360.0, Credit_History is None, Property_Area is Semiurban","- Gender : Male
3
+ - Married : Yes
4
+ - Dependents : 0
5
+ - Education : Graduate
6
+ - Self_Employed : No
7
+ - ApplicantIncome : 6000
8
+ - CoapplicantIncome : 2250.0
9
+ - LoanAmount : 265.0
10
+ - Loan_Amount_Term : 360.0
11
+ - Credit_History : None
12
+ - Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 6000. The CoapplicantIncome is 2250.0. The LoanAmount is 265.0. The Loan_Amount_Term is 360.0. The Credit_History is None. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
13
+ <thead>
14
+ <tr style=""text-align: right;"">
15
+ <th></th>
16
+ <th>Gender</th>
17
+ <th>Married</th>
18
+ <th>Dependents</th>
19
+ <th>Education</th>
20
+ <th>Self_Employed</th>
21
+ <th>ApplicantIncome</th>
22
+ <th>CoapplicantIncome</th>
23
+ <th>LoanAmount</th>
24
+ <th>Loan_Amount_Term</th>
25
+ <th>Credit_History</th>
26
+ <th>Property_Area</th>
27
+ </tr>
28
+ </thead>
29
+ <tbody>
30
+ <tr>
31
+ <th>0</th>
32
+ <td>Male</td>
33
+ <td>Yes</td>
34
+ <td>0</td>
35
+ <td>Graduate</td>
36
+ <td>No</td>
37
+ <td>6000</td>
38
+ <td>2250.0</td>
39
+ <td>265.0</td>
40
+ <td>360.0</td>
41
+ <td>None</td>
42
+ <td>Semiurban</td>
43
+ </tr>
44
+ </tbody>
45
+ </table>","\begin{tabular}{llllllrrrrll}
46
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
47
+ 0 & Male & Yes & 0 & Graduate & No & 6000 & 2250.000000 & 265.000000 & 360.000000 & None & Semiurban \\
48
+ \end{tabular}
49
+ ","{'ApplicantIncome': 6000, 'CoapplicantIncome': 2250.0, 'Credit_History': None, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 265.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 265.0 dollars for 30.0 months. He has unknown credit history. He is a graduate and is not self employed. He earns 6000 dollars and his co-applicant earns 2250.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
50
+ 8,Female,LP001639,Female,Yes,0,Graduate,No,3625,0.0,108.0,360.0,1.0,Semiurban,Y,"Gender is Female, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 3625, CoapplicantIncome is 0.0, LoanAmount is 108.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Female
51
+ - Married : Yes
52
+ - Dependents : 0
53
+ - Education : Graduate
54
+ - Self_Employed : No
55
+ - ApplicantIncome : 3625
56
+ - CoapplicantIncome : 0.0
57
+ - LoanAmount : 108.0
58
+ - Loan_Amount_Term : 360.0
59
+ - Credit_History : 1.0
60
+ - Property_Area : Semiurban",The Gender is Female. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 3625. The CoapplicantIncome is 0.0. The LoanAmount is 108.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
61
+ <thead>
62
+ <tr style=""text-align: right;"">
63
+ <th></th>
64
+ <th>Gender</th>
65
+ <th>Married</th>
66
+ <th>Dependents</th>
67
+ <th>Education</th>
68
+ <th>Self_Employed</th>
69
+ <th>ApplicantIncome</th>
70
+ <th>CoapplicantIncome</th>
71
+ <th>LoanAmount</th>
72
+ <th>Loan_Amount_Term</th>
73
+ <th>Credit_History</th>
74
+ <th>Property_Area</th>
75
+ </tr>
76
+ </thead>
77
+ <tbody>
78
+ <tr>
79
+ <th>0</th>
80
+ <td>Female</td>
81
+ <td>Yes</td>
82
+ <td>0</td>
83
+ <td>Graduate</td>
84
+ <td>No</td>
85
+ <td>3625</td>
86
+ <td>0.0</td>
87
+ <td>108.0</td>
88
+ <td>360.0</td>
89
+ <td>1.0</td>
90
+ <td>Semiurban</td>
91
+ </tr>
92
+ </tbody>
93
+ </table>","\begin{tabular}{llllllrrrrrl}
94
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
95
+ 0 & Female & Yes & 0 & Graduate & No & 3625 & 0.000000 & 108.000000 & 360.000000 & 1.000000 & Semiurban \\
96
+ \end{tabular}
97
+ ","{'ApplicantIncome': 3625, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Female', 'LoanAmount': 108.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married female individual is applying for a loan of 108.0 dollars for 30.0 months. She has a credit history. She is a graduate and is not self employed. She earns 3625 dollars. She has no person that she is liable to provide maintenance for. She lives in semiurban area.
98
+ 1,Male,LP001316,Male,Yes,0,Graduate,No,2958,2900.0,131.0,360.0,1.0,Semiurban,Y,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 2958, CoapplicantIncome is 2900.0, LoanAmount is 131.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Male
99
+ - Married : Yes
100
+ - Dependents : 0
101
+ - Education : Graduate
102
+ - Self_Employed : No
103
+ - ApplicantIncome : 2958
104
+ - CoapplicantIncome : 2900.0
105
+ - LoanAmount : 131.0
106
+ - Loan_Amount_Term : 360.0
107
+ - Credit_History : 1.0
108
+ - Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 2958. The CoapplicantIncome is 2900.0. The LoanAmount is 131.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
109
+ <thead>
110
+ <tr style=""text-align: right;"">
111
+ <th></th>
112
+ <th>Gender</th>
113
+ <th>Married</th>
114
+ <th>Dependents</th>
115
+ <th>Education</th>
116
+ <th>Self_Employed</th>
117
+ <th>ApplicantIncome</th>
118
+ <th>CoapplicantIncome</th>
119
+ <th>LoanAmount</th>
120
+ <th>Loan_Amount_Term</th>
121
+ <th>Credit_History</th>
122
+ <th>Property_Area</th>
123
+ </tr>
124
+ </thead>
125
+ <tbody>
126
+ <tr>
127
+ <th>0</th>
128
+ <td>Male</td>
129
+ <td>Yes</td>
130
+ <td>0</td>
131
+ <td>Graduate</td>
132
+ <td>No</td>
133
+ <td>2958</td>
134
+ <td>2900.0</td>
135
+ <td>131.0</td>
136
+ <td>360.0</td>
137
+ <td>1.0</td>
138
+ <td>Semiurban</td>
139
+ </tr>
140
+ </tbody>
141
+ </table>","\begin{tabular}{llllllrrrrrl}
142
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
143
+ 0 & Male & Yes & 0 & Graduate & No & 2958 & 2900.000000 & 131.000000 & 360.000000 & 1.000000 & Semiurban \\
144
+ \end{tabular}
145
+ ","{'ApplicantIncome': 2958, 'CoapplicantIncome': 2900.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 131.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 131.0 dollars for 30.0 months. He has a credit history. He is a graduate and is not self employed. He earns 2958 dollars and his co-applicant earns 2900.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
146
+ 19,Female,LP002367,Female,No,1,Not Graduate,No,4606,0.0,81.0,360.0,1.0,Rural,N,"Gender is Female, Married is No, Dependents is 1, Education is Not Graduate, Self_Employed is No, ApplicantIncome is 4606, CoapplicantIncome is 0.0, LoanAmount is 81.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Rural","- Gender : Female
147
+ - Married : No
148
+ - Dependents : 1
149
+ - Education : Not Graduate
150
+ - Self_Employed : No
151
+ - ApplicantIncome : 4606
152
+ - CoapplicantIncome : 0.0
153
+ - LoanAmount : 81.0
154
+ - Loan_Amount_Term : 360.0
155
+ - Credit_History : 1.0
156
+ - Property_Area : Rural",The Gender is Female. The Married is No. The Dependents is 1. The Education is Not Graduate. The Self_Employed is No. The ApplicantIncome is 4606. The CoapplicantIncome is 0.0. The LoanAmount is 81.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Rural,"<table border=""1"" class=""dataframe"">
157
+ <thead>
158
+ <tr style=""text-align: right;"">
159
+ <th></th>
160
+ <th>Gender</th>
161
+ <th>Married</th>
162
+ <th>Dependents</th>
163
+ <th>Education</th>
164
+ <th>Self_Employed</th>
165
+ <th>ApplicantIncome</th>
166
+ <th>CoapplicantIncome</th>
167
+ <th>LoanAmount</th>
168
+ <th>Loan_Amount_Term</th>
169
+ <th>Credit_History</th>
170
+ <th>Property_Area</th>
171
+ </tr>
172
+ </thead>
173
+ <tbody>
174
+ <tr>
175
+ <th>0</th>
176
+ <td>Female</td>
177
+ <td>No</td>
178
+ <td>1</td>
179
+ <td>Not Graduate</td>
180
+ <td>No</td>
181
+ <td>4606</td>
182
+ <td>0.0</td>
183
+ <td>81.0</td>
184
+ <td>360.0</td>
185
+ <td>1.0</td>
186
+ <td>Rural</td>
187
+ </tr>
188
+ </tbody>
189
+ </table>","\begin{tabular}{llllllrrrrrl}
190
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
191
+ 0 & Female & No & 1 & Not Graduate & No & 4606 & 0.000000 & 81.000000 & 360.000000 & 1.000000 & Rural \\
192
+ \end{tabular}
193
+ ","{'ApplicantIncome': 4606, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '1', 'Education': 'Not Graduate', 'Gender': 'Female', 'LoanAmount': 81.0, 'Loan_Amount_Term': 360.0, 'Married': 'No', 'Property_Area': 'Rural', 'Self_Employed': 'No'}",A unmarried female individual is applying for a loan of 81.0 dollars for 30.0 months. She has a credit history. She is not a graduate and is not self employed. She earns 4606 dollars. She has 1 person that she is liable to provide maintenance for. She lives in rural area.
194
+ 2,Male,LP001758,Male,Yes,2,Graduate,No,6250,1695.0,210.0,360.0,1.0,Semiurban,Y,"Gender is Male, Married is Yes, Dependents is 2, Education is Graduate, Self_Employed is No, ApplicantIncome is 6250, CoapplicantIncome is 1695.0, LoanAmount is 210.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Male
195
+ - Married : Yes
196
+ - Dependents : 2
197
+ - Education : Graduate
198
+ - Self_Employed : No
199
+ - ApplicantIncome : 6250
200
+ - CoapplicantIncome : 1695.0
201
+ - LoanAmount : 210.0
202
+ - Loan_Amount_Term : 360.0
203
+ - Credit_History : 1.0
204
+ - Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 2. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 6250. The CoapplicantIncome is 1695.0. The LoanAmount is 210.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
205
+ <thead>
206
+ <tr style=""text-align: right;"">
207
+ <th></th>
208
+ <th>Gender</th>
209
+ <th>Married</th>
210
+ <th>Dependents</th>
211
+ <th>Education</th>
212
+ <th>Self_Employed</th>
213
+ <th>ApplicantIncome</th>
214
+ <th>CoapplicantIncome</th>
215
+ <th>LoanAmount</th>
216
+ <th>Loan_Amount_Term</th>
217
+ <th>Credit_History</th>
218
+ <th>Property_Area</th>
219
+ </tr>
220
+ </thead>
221
+ <tbody>
222
+ <tr>
223
+ <th>0</th>
224
+ <td>Male</td>
225
+ <td>Yes</td>
226
+ <td>2</td>
227
+ <td>Graduate</td>
228
+ <td>No</td>
229
+ <td>6250</td>
230
+ <td>1695.0</td>
231
+ <td>210.0</td>
232
+ <td>360.0</td>
233
+ <td>1.0</td>
234
+ <td>Semiurban</td>
235
+ </tr>
236
+ </tbody>
237
+ </table>","\begin{tabular}{llllllrrrrrl}
238
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
239
+ 0 & Male & Yes & 2 & Graduate & No & 6250 & 1695.000000 & 210.000000 & 360.000000 & 1.000000 & Semiurban \\
240
+ \end{tabular}
241
+ ","{'ApplicantIncome': 6250, 'CoapplicantIncome': 1695.0, 'Credit_History': 1.0, 'Dependents': '2', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 210.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 210.0 dollars for 30.0 months. He has a credit history. He is a graduate and is not self employed. He earns 6250 dollars and his co-applicant earns 1695.0 dollars. He has 2 people that he is liable to provide maintenance for. He lives in semiurban area.
242
+ 20,Female,LP002949,Female,No,3+,Graduate,,416,41667.0,350.0,180.0,,Urban,N,"Gender is Female, Married is No, Dependents is 3+, Education is Graduate, Self_Employed is None, ApplicantIncome is 416, CoapplicantIncome is 41667.0, LoanAmount is 350.0, Loan_Amount_Term is 180.0, Credit_History is None, Property_Area is Urban","- Gender : Female
243
+ - Married : No
244
+ - Dependents : 3+
245
+ - Education : Graduate
246
+ - Self_Employed : None
247
+ - ApplicantIncome : 416
248
+ - CoapplicantIncome : 41667.0
249
+ - LoanAmount : 350.0
250
+ - Loan_Amount_Term : 180.0
251
+ - Credit_History : None
252
+ - Property_Area : Urban",The Gender is Female. The Married is No. The Dependents is 3+. The Education is Graduate. The Self_Employed is None. The ApplicantIncome is 416. The CoapplicantIncome is 41667.0. The LoanAmount is 350.0. The Loan_Amount_Term is 180.0. The Credit_History is None. The Property_Area is Urban,"<table border=""1"" class=""dataframe"">
253
+ <thead>
254
+ <tr style=""text-align: right;"">
255
+ <th></th>
256
+ <th>Gender</th>
257
+ <th>Married</th>
258
+ <th>Dependents</th>
259
+ <th>Education</th>
260
+ <th>Self_Employed</th>
261
+ <th>ApplicantIncome</th>
262
+ <th>CoapplicantIncome</th>
263
+ <th>LoanAmount</th>
264
+ <th>Loan_Amount_Term</th>
265
+ <th>Credit_History</th>
266
+ <th>Property_Area</th>
267
+ </tr>
268
+ </thead>
269
+ <tbody>
270
+ <tr>
271
+ <th>0</th>
272
+ <td>Female</td>
273
+ <td>No</td>
274
+ <td>3+</td>
275
+ <td>Graduate</td>
276
+ <td>None</td>
277
+ <td>416</td>
278
+ <td>41667.0</td>
279
+ <td>350.0</td>
280
+ <td>180.0</td>
281
+ <td>None</td>
282
+ <td>Urban</td>
283
+ </tr>
284
+ </tbody>
285
+ </table>","\begin{tabular}{llllllrrrrll}
286
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
287
+ 0 & Female & No & 3+ & Graduate & None & 416 & 41667.000000 & 350.000000 & 180.000000 & None & Urban \\
288
+ \end{tabular}
289
+ ","{'ApplicantIncome': 416, 'CoapplicantIncome': 41667.0, 'Credit_History': None, 'Dependents': '3+', 'Education': 'Graduate', 'Gender': 'Female', 'LoanAmount': 350.0, 'Loan_Amount_Term': 180.0, 'Married': 'No', 'Property_Area': 'Urban', 'Self_Employed': None}",A unmarried female individual is applying for a loan of 350.0 dollars for 15.0 months. She has unknown credit history. She is a graduate and has unknown self employment status. She earns 416 dollars and her co-applicant earns 41667.0 dollars. She has 3+ people that she is liable to provide maintenance for. She lives in urban area.
290
+ 3,Male,LP002537,Male,Yes,0,Graduate,No,2083,3150.0,128.0,360.0,1.0,Semiurban,Y,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 2083, CoapplicantIncome is 3150.0, LoanAmount is 128.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Male
291
+ - Married : Yes
292
+ - Dependents : 0
293
+ - Education : Graduate
294
+ - Self_Employed : No
295
+ - ApplicantIncome : 2083
296
+ - CoapplicantIncome : 3150.0
297
+ - LoanAmount : 128.0
298
+ - Loan_Amount_Term : 360.0
299
+ - Credit_History : 1.0
300
+ - Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 2083. The CoapplicantIncome is 3150.0. The LoanAmount is 128.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
301
+ <thead>
302
+ <tr style=""text-align: right;"">
303
+ <th></th>
304
+ <th>Gender</th>
305
+ <th>Married</th>
306
+ <th>Dependents</th>
307
+ <th>Education</th>
308
+ <th>Self_Employed</th>
309
+ <th>ApplicantIncome</th>
310
+ <th>CoapplicantIncome</th>
311
+ <th>LoanAmount</th>
312
+ <th>Loan_Amount_Term</th>
313
+ <th>Credit_History</th>
314
+ <th>Property_Area</th>
315
+ </tr>
316
+ </thead>
317
+ <tbody>
318
+ <tr>
319
+ <th>0</th>
320
+ <td>Male</td>
321
+ <td>Yes</td>
322
+ <td>0</td>
323
+ <td>Graduate</td>
324
+ <td>No</td>
325
+ <td>2083</td>
326
+ <td>3150.0</td>
327
+ <td>128.0</td>
328
+ <td>360.0</td>
329
+ <td>1.0</td>
330
+ <td>Semiurban</td>
331
+ </tr>
332
+ </tbody>
333
+ </table>","\begin{tabular}{llllllrrrrrl}
334
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
335
+ 0 & Male & Yes & 0 & Graduate & No & 2083 & 3150.000000 & 128.000000 & 360.000000 & 1.000000 & Semiurban \\
336
+ \end{tabular}
337
+ ","{'ApplicantIncome': 2083, 'CoapplicantIncome': 3150.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 128.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 128.0 dollars for 30.0 months. He has a credit history. He is a graduate and is not self employed. He earns 2083 dollars and his co-applicant earns 3150.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
338
+ 27,Female,LP002502,Female,Yes,2,Not Graduate,,210,2917.0,98.0,360.0,1.0,Semiurban,Y,"Gender is Female, Married is Yes, Dependents is 2, Education is Not Graduate, Self_Employed is None, ApplicantIncome is 210, CoapplicantIncome is 2917.0, LoanAmount is 98.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Female
339
+ - Married : Yes
340
+ - Dependents : 2
341
+ - Education : Not Graduate
342
+ - Self_Employed : None
343
+ - ApplicantIncome : 210
344
+ - CoapplicantIncome : 2917.0
345
+ - LoanAmount : 98.0
346
+ - Loan_Amount_Term : 360.0
347
+ - Credit_History : 1.0
348
+ - Property_Area : Semiurban",The Gender is Female. The Married is Yes. The Dependents is 2. The Education is Not Graduate. The Self_Employed is None. The ApplicantIncome is 210. The CoapplicantIncome is 2917.0. The LoanAmount is 98.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
349
+ <thead>
350
+ <tr style=""text-align: right;"">
351
+ <th></th>
352
+ <th>Gender</th>
353
+ <th>Married</th>
354
+ <th>Dependents</th>
355
+ <th>Education</th>
356
+ <th>Self_Employed</th>
357
+ <th>ApplicantIncome</th>
358
+ <th>CoapplicantIncome</th>
359
+ <th>LoanAmount</th>
360
+ <th>Loan_Amount_Term</th>
361
+ <th>Credit_History</th>
362
+ <th>Property_Area</th>
363
+ </tr>
364
+ </thead>
365
+ <tbody>
366
+ <tr>
367
+ <th>0</th>
368
+ <td>Female</td>
369
+ <td>Yes</td>
370
+ <td>2</td>
371
+ <td>Not Graduate</td>
372
+ <td>None</td>
373
+ <td>210</td>
374
+ <td>2917.0</td>
375
+ <td>98.0</td>
376
+ <td>360.0</td>
377
+ <td>1.0</td>
378
+ <td>Semiurban</td>
379
+ </tr>
380
+ </tbody>
381
+ </table>","\begin{tabular}{llllllrrrrrl}
382
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
383
+ 0 & Female & Yes & 2 & Not Graduate & None & 210 & 2917.000000 & 98.000000 & 360.000000 & 1.000000 & Semiurban \\
384
+ \end{tabular}
385
+ ","{'ApplicantIncome': 210, 'CoapplicantIncome': 2917.0, 'Credit_History': 1.0, 'Dependents': '2', 'Education': 'Not Graduate', 'Gender': 'Female', 'LoanAmount': 98.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': None}",A married female individual is applying for a loan of 98.0 dollars for 30.0 months. She has a credit history. She is not a graduate and has unknown self employment status. She earns 210 dollars and her co-applicant earns 2917.0 dollars. She has 2 people that she is liable to provide maintenance for. She lives in semiurban area.
new_data/loan_pred-fewshot.csv ADDED
@@ -0,0 +1,481 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Unnamed: 0,Gender,Loan_ID,Gender.1,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_Status,great,list,text,html,latex,json,LIFT
2
+ 0,Male,LP001273,Male,Yes,0,Graduate,No,6000,2250.0,265.0,360.0,,Semiurban,N,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 6000, CoapplicantIncome is 2250.0, LoanAmount is 265.0, Loan_Amount_Term is 360.0, Credit_History is None, Property_Area is Semiurban","- Gender : Male
3
+ - Married : Yes
4
+ - Dependents : 0
5
+ - Education : Graduate
6
+ - Self_Employed : No
7
+ - ApplicantIncome : 6000
8
+ - CoapplicantIncome : 2250.0
9
+ - LoanAmount : 265.0
10
+ - Loan_Amount_Term : 360.0
11
+ - Credit_History : None
12
+ - Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 6000. The CoapplicantIncome is 2250.0. The LoanAmount is 265.0. The Loan_Amount_Term is 360.0. The Credit_History is None. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
13
+ <thead>
14
+ <tr style=""text-align: right;"">
15
+ <th></th>
16
+ <th>Gender</th>
17
+ <th>Married</th>
18
+ <th>Dependents</th>
19
+ <th>Education</th>
20
+ <th>Self_Employed</th>
21
+ <th>ApplicantIncome</th>
22
+ <th>CoapplicantIncome</th>
23
+ <th>LoanAmount</th>
24
+ <th>Loan_Amount_Term</th>
25
+ <th>Credit_History</th>
26
+ <th>Property_Area</th>
27
+ </tr>
28
+ </thead>
29
+ <tbody>
30
+ <tr>
31
+ <th>0</th>
32
+ <td>Male</td>
33
+ <td>Yes</td>
34
+ <td>0</td>
35
+ <td>Graduate</td>
36
+ <td>No</td>
37
+ <td>6000</td>
38
+ <td>2250.0</td>
39
+ <td>265.0</td>
40
+ <td>360.0</td>
41
+ <td>None</td>
42
+ <td>Semiurban</td>
43
+ </tr>
44
+ </tbody>
45
+ </table>","\begin{tabular}{llllllrrrrll}
46
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
47
+ 0 & Male & Yes & 0 & Graduate & No & 6000 & 2250.000000 & 265.000000 & 360.000000 & None & Semiurban \\
48
+ \end{tabular}
49
+ ","{'ApplicantIncome': 6000, 'CoapplicantIncome': 2250.0, 'Credit_History': None, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 265.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 265.0 dollars for 30.0 months. He has unknown credit history. He is a graduate and is not self employed. He earns 6000 dollars and his co-applicant earns 2250.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
50
+ 8,Female,LP001639,Female,Yes,0,Graduate,No,3625,0.0,108.0,360.0,1.0,Semiurban,Y,"Gender is Female, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 3625, CoapplicantIncome is 0.0, LoanAmount is 108.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Female
51
+ - Married : Yes
52
+ - Dependents : 0
53
+ - Education : Graduate
54
+ - Self_Employed : No
55
+ - ApplicantIncome : 3625
56
+ - CoapplicantIncome : 0.0
57
+ - LoanAmount : 108.0
58
+ - Loan_Amount_Term : 360.0
59
+ - Credit_History : 1.0
60
+ - Property_Area : Semiurban",The Gender is Female. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 3625. The CoapplicantIncome is 0.0. The LoanAmount is 108.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
61
+ <thead>
62
+ <tr style=""text-align: right;"">
63
+ <th></th>
64
+ <th>Gender</th>
65
+ <th>Married</th>
66
+ <th>Dependents</th>
67
+ <th>Education</th>
68
+ <th>Self_Employed</th>
69
+ <th>ApplicantIncome</th>
70
+ <th>CoapplicantIncome</th>
71
+ <th>LoanAmount</th>
72
+ <th>Loan_Amount_Term</th>
73
+ <th>Credit_History</th>
74
+ <th>Property_Area</th>
75
+ </tr>
76
+ </thead>
77
+ <tbody>
78
+ <tr>
79
+ <th>0</th>
80
+ <td>Female</td>
81
+ <td>Yes</td>
82
+ <td>0</td>
83
+ <td>Graduate</td>
84
+ <td>No</td>
85
+ <td>3625</td>
86
+ <td>0.0</td>
87
+ <td>108.0</td>
88
+ <td>360.0</td>
89
+ <td>1.0</td>
90
+ <td>Semiurban</td>
91
+ </tr>
92
+ </tbody>
93
+ </table>","\begin{tabular}{llllllrrrrrl}
94
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
95
+ 0 & Female & Yes & 0 & Graduate & No & 3625 & 0.000000 & 108.000000 & 360.000000 & 1.000000 & Semiurban \\
96
+ \end{tabular}
97
+ ","{'ApplicantIncome': 3625, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Female', 'LoanAmount': 108.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married female individual is applying for a loan of 108.0 dollars for 30.0 months. She has a credit history. She is a graduate and is not self employed. She earns 3625 dollars. She has no person that she is liable to provide maintenance for. She lives in semiurban area.
98
+ 1,Male,LP001316,Male,Yes,0,Graduate,No,2958,2900.0,131.0,360.0,1.0,Semiurban,Y,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 2958, CoapplicantIncome is 2900.0, LoanAmount is 131.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Male
99
+ - Married : Yes
100
+ - Dependents : 0
101
+ - Education : Graduate
102
+ - Self_Employed : No
103
+ - ApplicantIncome : 2958
104
+ - CoapplicantIncome : 2900.0
105
+ - LoanAmount : 131.0
106
+ - Loan_Amount_Term : 360.0
107
+ - Credit_History : 1.0
108
+ - Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 2958. The CoapplicantIncome is 2900.0. The LoanAmount is 131.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
109
+ <thead>
110
+ <tr style=""text-align: right;"">
111
+ <th></th>
112
+ <th>Gender</th>
113
+ <th>Married</th>
114
+ <th>Dependents</th>
115
+ <th>Education</th>
116
+ <th>Self_Employed</th>
117
+ <th>ApplicantIncome</th>
118
+ <th>CoapplicantIncome</th>
119
+ <th>LoanAmount</th>
120
+ <th>Loan_Amount_Term</th>
121
+ <th>Credit_History</th>
122
+ <th>Property_Area</th>
123
+ </tr>
124
+ </thead>
125
+ <tbody>
126
+ <tr>
127
+ <th>0</th>
128
+ <td>Male</td>
129
+ <td>Yes</td>
130
+ <td>0</td>
131
+ <td>Graduate</td>
132
+ <td>No</td>
133
+ <td>2958</td>
134
+ <td>2900.0</td>
135
+ <td>131.0</td>
136
+ <td>360.0</td>
137
+ <td>1.0</td>
138
+ <td>Semiurban</td>
139
+ </tr>
140
+ </tbody>
141
+ </table>","\begin{tabular}{llllllrrrrrl}
142
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
143
+ 0 & Male & Yes & 0 & Graduate & No & 2958 & 2900.000000 & 131.000000 & 360.000000 & 1.000000 & Semiurban \\
144
+ \end{tabular}
145
+ ","{'ApplicantIncome': 2958, 'CoapplicantIncome': 2900.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 131.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 131.0 dollars for 30.0 months. He has a credit history. He is a graduate and is not self employed. He earns 2958 dollars and his co-applicant earns 2900.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
146
+ 19,Female,LP002367,Female,No,1,Not Graduate,No,4606,0.0,81.0,360.0,1.0,Rural,N,"Gender is Female, Married is No, Dependents is 1, Education is Not Graduate, Self_Employed is No, ApplicantIncome is 4606, CoapplicantIncome is 0.0, LoanAmount is 81.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Rural","- Gender : Female
147
+ - Married : No
148
+ - Dependents : 1
149
+ - Education : Not Graduate
150
+ - Self_Employed : No
151
+ - ApplicantIncome : 4606
152
+ - CoapplicantIncome : 0.0
153
+ - LoanAmount : 81.0
154
+ - Loan_Amount_Term : 360.0
155
+ - Credit_History : 1.0
156
+ - Property_Area : Rural",The Gender is Female. The Married is No. The Dependents is 1. The Education is Not Graduate. The Self_Employed is No. The ApplicantIncome is 4606. The CoapplicantIncome is 0.0. The LoanAmount is 81.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Rural,"<table border=""1"" class=""dataframe"">
157
+ <thead>
158
+ <tr style=""text-align: right;"">
159
+ <th></th>
160
+ <th>Gender</th>
161
+ <th>Married</th>
162
+ <th>Dependents</th>
163
+ <th>Education</th>
164
+ <th>Self_Employed</th>
165
+ <th>ApplicantIncome</th>
166
+ <th>CoapplicantIncome</th>
167
+ <th>LoanAmount</th>
168
+ <th>Loan_Amount_Term</th>
169
+ <th>Credit_History</th>
170
+ <th>Property_Area</th>
171
+ </tr>
172
+ </thead>
173
+ <tbody>
174
+ <tr>
175
+ <th>0</th>
176
+ <td>Female</td>
177
+ <td>No</td>
178
+ <td>1</td>
179
+ <td>Not Graduate</td>
180
+ <td>No</td>
181
+ <td>4606</td>
182
+ <td>0.0</td>
183
+ <td>81.0</td>
184
+ <td>360.0</td>
185
+ <td>1.0</td>
186
+ <td>Rural</td>
187
+ </tr>
188
+ </tbody>
189
+ </table>","\begin{tabular}{llllllrrrrrl}
190
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
191
+ 0 & Female & No & 1 & Not Graduate & No & 4606 & 0.000000 & 81.000000 & 360.000000 & 1.000000 & Rural \\
192
+ \end{tabular}
193
+ ","{'ApplicantIncome': 4606, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '1', 'Education': 'Not Graduate', 'Gender': 'Female', 'LoanAmount': 81.0, 'Loan_Amount_Term': 360.0, 'Married': 'No', 'Property_Area': 'Rural', 'Self_Employed': 'No'}",A unmarried female individual is applying for a loan of 81.0 dollars for 30.0 months. She has a credit history. She is not a graduate and is not self employed. She earns 4606 dollars. She has 1 person that she is liable to provide maintenance for. She lives in rural area.
194
+ 2,Male,LP001758,Male,Yes,2,Graduate,No,6250,1695.0,210.0,360.0,1.0,Semiurban,Y,"Gender is Male, Married is Yes, Dependents is 2, Education is Graduate, Self_Employed is No, ApplicantIncome is 6250, CoapplicantIncome is 1695.0, LoanAmount is 210.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Male
195
+ - Married : Yes
196
+ - Dependents : 2
197
+ - Education : Graduate
198
+ - Self_Employed : No
199
+ - ApplicantIncome : 6250
200
+ - CoapplicantIncome : 1695.0
201
+ - LoanAmount : 210.0
202
+ - Loan_Amount_Term : 360.0
203
+ - Credit_History : 1.0
204
+ - Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 2. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 6250. The CoapplicantIncome is 1695.0. The LoanAmount is 210.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
205
+ <thead>
206
+ <tr style=""text-align: right;"">
207
+ <th></th>
208
+ <th>Gender</th>
209
+ <th>Married</th>
210
+ <th>Dependents</th>
211
+ <th>Education</th>
212
+ <th>Self_Employed</th>
213
+ <th>ApplicantIncome</th>
214
+ <th>CoapplicantIncome</th>
215
+ <th>LoanAmount</th>
216
+ <th>Loan_Amount_Term</th>
217
+ <th>Credit_History</th>
218
+ <th>Property_Area</th>
219
+ </tr>
220
+ </thead>
221
+ <tbody>
222
+ <tr>
223
+ <th>0</th>
224
+ <td>Male</td>
225
+ <td>Yes</td>
226
+ <td>2</td>
227
+ <td>Graduate</td>
228
+ <td>No</td>
229
+ <td>6250</td>
230
+ <td>1695.0</td>
231
+ <td>210.0</td>
232
+ <td>360.0</td>
233
+ <td>1.0</td>
234
+ <td>Semiurban</td>
235
+ </tr>
236
+ </tbody>
237
+ </table>","\begin{tabular}{llllllrrrrrl}
238
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
239
+ 0 & Male & Yes & 2 & Graduate & No & 6250 & 1695.000000 & 210.000000 & 360.000000 & 1.000000 & Semiurban \\
240
+ \end{tabular}
241
+ ","{'ApplicantIncome': 6250, 'CoapplicantIncome': 1695.0, 'Credit_History': 1.0, 'Dependents': '2', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 210.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 210.0 dollars for 30.0 months. He has a credit history. He is a graduate and is not self employed. He earns 6250 dollars and his co-applicant earns 1695.0 dollars. He has 2 people that he is liable to provide maintenance for. He lives in semiurban area.
242
+ 20,Female,LP002949,Female,No,3+,Graduate,,416,41667.0,350.0,180.0,,Urban,N,"Gender is Female, Married is No, Dependents is 3+, Education is Graduate, Self_Employed is None, ApplicantIncome is 416, CoapplicantIncome is 41667.0, LoanAmount is 350.0, Loan_Amount_Term is 180.0, Credit_History is None, Property_Area is Urban","- Gender : Female
243
+ - Married : No
244
+ - Dependents : 3+
245
+ - Education : Graduate
246
+ - Self_Employed : None
247
+ - ApplicantIncome : 416
248
+ - CoapplicantIncome : 41667.0
249
+ - LoanAmount : 350.0
250
+ - Loan_Amount_Term : 180.0
251
+ - Credit_History : None
252
+ - Property_Area : Urban",The Gender is Female. The Married is No. The Dependents is 3+. The Education is Graduate. The Self_Employed is None. The ApplicantIncome is 416. The CoapplicantIncome is 41667.0. The LoanAmount is 350.0. The Loan_Amount_Term is 180.0. The Credit_History is None. The Property_Area is Urban,"<table border=""1"" class=""dataframe"">
253
+ <thead>
254
+ <tr style=""text-align: right;"">
255
+ <th></th>
256
+ <th>Gender</th>
257
+ <th>Married</th>
258
+ <th>Dependents</th>
259
+ <th>Education</th>
260
+ <th>Self_Employed</th>
261
+ <th>ApplicantIncome</th>
262
+ <th>CoapplicantIncome</th>
263
+ <th>LoanAmount</th>
264
+ <th>Loan_Amount_Term</th>
265
+ <th>Credit_History</th>
266
+ <th>Property_Area</th>
267
+ </tr>
268
+ </thead>
269
+ <tbody>
270
+ <tr>
271
+ <th>0</th>
272
+ <td>Female</td>
273
+ <td>No</td>
274
+ <td>3+</td>
275
+ <td>Graduate</td>
276
+ <td>None</td>
277
+ <td>416</td>
278
+ <td>41667.0</td>
279
+ <td>350.0</td>
280
+ <td>180.0</td>
281
+ <td>None</td>
282
+ <td>Urban</td>
283
+ </tr>
284
+ </tbody>
285
+ </table>","\begin{tabular}{llllllrrrrll}
286
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
287
+ 0 & Female & No & 3+ & Graduate & None & 416 & 41667.000000 & 350.000000 & 180.000000 & None & Urban \\
288
+ \end{tabular}
289
+ ","{'ApplicantIncome': 416, 'CoapplicantIncome': 41667.0, 'Credit_History': None, 'Dependents': '3+', 'Education': 'Graduate', 'Gender': 'Female', 'LoanAmount': 350.0, 'Loan_Amount_Term': 180.0, 'Married': 'No', 'Property_Area': 'Urban', 'Self_Employed': None}",A unmarried female individual is applying for a loan of 350.0 dollars for 15.0 months. She has unknown credit history. She is a graduate and has unknown self employment status. She earns 416 dollars and her co-applicant earns 41667.0 dollars. She has 3+ people that she is liable to provide maintenance for. She lives in urban area.
290
+ 3,Male,LP002537,Male,Yes,0,Graduate,No,2083,3150.0,128.0,360.0,1.0,Semiurban,Y,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 2083, CoapplicantIncome is 3150.0, LoanAmount is 128.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Male
291
+ - Married : Yes
292
+ - Dependents : 0
293
+ - Education : Graduate
294
+ - Self_Employed : No
295
+ - ApplicantIncome : 2083
296
+ - CoapplicantIncome : 3150.0
297
+ - LoanAmount : 128.0
298
+ - Loan_Amount_Term : 360.0
299
+ - Credit_History : 1.0
300
+ - Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 2083. The CoapplicantIncome is 3150.0. The LoanAmount is 128.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
301
+ <thead>
302
+ <tr style=""text-align: right;"">
303
+ <th></th>
304
+ <th>Gender</th>
305
+ <th>Married</th>
306
+ <th>Dependents</th>
307
+ <th>Education</th>
308
+ <th>Self_Employed</th>
309
+ <th>ApplicantIncome</th>
310
+ <th>CoapplicantIncome</th>
311
+ <th>LoanAmount</th>
312
+ <th>Loan_Amount_Term</th>
313
+ <th>Credit_History</th>
314
+ <th>Property_Area</th>
315
+ </tr>
316
+ </thead>
317
+ <tbody>
318
+ <tr>
319
+ <th>0</th>
320
+ <td>Male</td>
321
+ <td>Yes</td>
322
+ <td>0</td>
323
+ <td>Graduate</td>
324
+ <td>No</td>
325
+ <td>2083</td>
326
+ <td>3150.0</td>
327
+ <td>128.0</td>
328
+ <td>360.0</td>
329
+ <td>1.0</td>
330
+ <td>Semiurban</td>
331
+ </tr>
332
+ </tbody>
333
+ </table>","\begin{tabular}{llllllrrrrrl}
334
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
335
+ 0 & Male & Yes & 0 & Graduate & No & 2083 & 3150.000000 & 128.000000 & 360.000000 & 1.000000 & Semiurban \\
336
+ \end{tabular}
337
+ ","{'ApplicantIncome': 2083, 'CoapplicantIncome': 3150.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 128.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 128.0 dollars for 30.0 months. He has a credit history. He is a graduate and is not self employed. He earns 2083 dollars and his co-applicant earns 3150.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
338
+ 27,Female,LP002502,Female,Yes,2,Not Graduate,,210,2917.0,98.0,360.0,1.0,Semiurban,Y,"Gender is Female, Married is Yes, Dependents is 2, Education is Not Graduate, Self_Employed is None, ApplicantIncome is 210, CoapplicantIncome is 2917.0, LoanAmount is 98.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Female
339
+ - Married : Yes
340
+ - Dependents : 2
341
+ - Education : Not Graduate
342
+ - Self_Employed : None
343
+ - ApplicantIncome : 210
344
+ - CoapplicantIncome : 2917.0
345
+ - LoanAmount : 98.0
346
+ - Loan_Amount_Term : 360.0
347
+ - Credit_History : 1.0
348
+ - Property_Area : Semiurban",The Gender is Female. The Married is Yes. The Dependents is 2. The Education is Not Graduate. The Self_Employed is None. The ApplicantIncome is 210. The CoapplicantIncome is 2917.0. The LoanAmount is 98.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
349
+ <thead>
350
+ <tr style=""text-align: right;"">
351
+ <th></th>
352
+ <th>Gender</th>
353
+ <th>Married</th>
354
+ <th>Dependents</th>
355
+ <th>Education</th>
356
+ <th>Self_Employed</th>
357
+ <th>ApplicantIncome</th>
358
+ <th>CoapplicantIncome</th>
359
+ <th>LoanAmount</th>
360
+ <th>Loan_Amount_Term</th>
361
+ <th>Credit_History</th>
362
+ <th>Property_Area</th>
363
+ </tr>
364
+ </thead>
365
+ <tbody>
366
+ <tr>
367
+ <th>0</th>
368
+ <td>Female</td>
369
+ <td>Yes</td>
370
+ <td>2</td>
371
+ <td>Not Graduate</td>
372
+ <td>None</td>
373
+ <td>210</td>
374
+ <td>2917.0</td>
375
+ <td>98.0</td>
376
+ <td>360.0</td>
377
+ <td>1.0</td>
378
+ <td>Semiurban</td>
379
+ </tr>
380
+ </tbody>
381
+ </table>","\begin{tabular}{llllllrrrrrl}
382
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
383
+ 0 & Female & Yes & 2 & Not Graduate & None & 210 & 2917.000000 & 98.000000 & 360.000000 & 1.000000 & Semiurban \\
384
+ \end{tabular}
385
+ ","{'ApplicantIncome': 210, 'CoapplicantIncome': 2917.0, 'Credit_History': 1.0, 'Dependents': '2', 'Education': 'Not Graduate', 'Gender': 'Female', 'LoanAmount': 98.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': None}",A married female individual is applying for a loan of 98.0 dollars for 30.0 months. She has a credit history. She is not a graduate and has unknown self employment status. She earns 210 dollars and her co-applicant earns 2917.0 dollars. She has 2 people that she is liable to provide maintenance for. She lives in semiurban area.
386
+ 4,Male,LP002493,Male,No,0,Graduate,No,4166,0.0,98.0,360.0,0.0,Semiurban,N,"Gender is Male, Married is No, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 4166, CoapplicantIncome is 0.0, LoanAmount is 98.0, Loan_Amount_Term is 360.0, Credit_History is 0.0, Property_Area is Semiurban","- Gender : Male
387
+ - Married : No
388
+ - Dependents : 0
389
+ - Education : Graduate
390
+ - Self_Employed : No
391
+ - ApplicantIncome : 4166
392
+ - CoapplicantIncome : 0.0
393
+ - LoanAmount : 98.0
394
+ - Loan_Amount_Term : 360.0
395
+ - Credit_History : 0.0
396
+ - Property_Area : Semiurban",The Gender is Male. The Married is No. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 4166. The CoapplicantIncome is 0.0. The LoanAmount is 98.0. The Loan_Amount_Term is 360.0. The Credit_History is 0.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
397
+ <thead>
398
+ <tr style=""text-align: right;"">
399
+ <th></th>
400
+ <th>Gender</th>
401
+ <th>Married</th>
402
+ <th>Dependents</th>
403
+ <th>Education</th>
404
+ <th>Self_Employed</th>
405
+ <th>ApplicantIncome</th>
406
+ <th>CoapplicantIncome</th>
407
+ <th>LoanAmount</th>
408
+ <th>Loan_Amount_Term</th>
409
+ <th>Credit_History</th>
410
+ <th>Property_Area</th>
411
+ </tr>
412
+ </thead>
413
+ <tbody>
414
+ <tr>
415
+ <th>0</th>
416
+ <td>Male</td>
417
+ <td>No</td>
418
+ <td>0</td>
419
+ <td>Graduate</td>
420
+ <td>No</td>
421
+ <td>4166</td>
422
+ <td>0.0</td>
423
+ <td>98.0</td>
424
+ <td>360.0</td>
425
+ <td>0.0</td>
426
+ <td>Semiurban</td>
427
+ </tr>
428
+ </tbody>
429
+ </table>","\begin{tabular}{llllllrrrrrl}
430
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
431
+ 0 & Male & No & 0 & Graduate & No & 4166 & 0.000000 & 98.000000 & 360.000000 & 0.000000 & Semiurban \\
432
+ \end{tabular}
433
+ ","{'ApplicantIncome': 4166, 'CoapplicantIncome': 0.0, 'Credit_History': 0.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 98.0, 'Loan_Amount_Term': 360.0, 'Married': 'No', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A unmarried male individual is applying for a loan of 98.0 dollars for 30.0 months. He does not have a credit history. He is a graduate and is not self employed. He earns 4166 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
434
+ 28,Female,LP002894,Female,Yes,0,Graduate,No,3166,0.0,36.0,360.0,1.0,Semiurban,Y,"Gender is Female, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 3166, CoapplicantIncome is 0.0, LoanAmount is 36.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Female
435
+ - Married : Yes
436
+ - Dependents : 0
437
+ - Education : Graduate
438
+ - Self_Employed : No
439
+ - ApplicantIncome : 3166
440
+ - CoapplicantIncome : 0.0
441
+ - LoanAmount : 36.0
442
+ - Loan_Amount_Term : 360.0
443
+ - Credit_History : 1.0
444
+ - Property_Area : Semiurban",The Gender is Female. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 3166. The CoapplicantIncome is 0.0. The LoanAmount is 36.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
445
+ <thead>
446
+ <tr style=""text-align: right;"">
447
+ <th></th>
448
+ <th>Gender</th>
449
+ <th>Married</th>
450
+ <th>Dependents</th>
451
+ <th>Education</th>
452
+ <th>Self_Employed</th>
453
+ <th>ApplicantIncome</th>
454
+ <th>CoapplicantIncome</th>
455
+ <th>LoanAmount</th>
456
+ <th>Loan_Amount_Term</th>
457
+ <th>Credit_History</th>
458
+ <th>Property_Area</th>
459
+ </tr>
460
+ </thead>
461
+ <tbody>
462
+ <tr>
463
+ <th>0</th>
464
+ <td>Female</td>
465
+ <td>Yes</td>
466
+ <td>0</td>
467
+ <td>Graduate</td>
468
+ <td>No</td>
469
+ <td>3166</td>
470
+ <td>0.0</td>
471
+ <td>36.0</td>
472
+ <td>360.0</td>
473
+ <td>1.0</td>
474
+ <td>Semiurban</td>
475
+ </tr>
476
+ </tbody>
477
+ </table>","\begin{tabular}{llllllrrrrrl}
478
+ & Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
479
+ 0 & Female & Yes & 0 & Graduate & No & 3166 & 0.000000 & 36.000000 & 360.000000 & 1.000000 & Semiurban \\
480
+ \end{tabular}
481
+ ","{'ApplicantIncome': 3166, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Female', 'LoanAmount': 36.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married female individual is applying for a loan of 36.0 dollars for 30.0 months. She has a credit history. She is a graduate and is not self employed. She earns 3166 dollars. She has no person that she is liable to provide maintenance for. She lives in semiurban area.
new_data/loan_pred-test.csv ADDED
The diff for this file is too large to render. See raw diff
 
new_data/loan_pred-train.csv ADDED
The diff for this file is too large to render. See raw diff
 
test/german_test.csv ADDED
@@ -0,0 +1,201 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ gender,checking_status,duration,credit_history,purpose,credit_amount,savings_status,employment,installment_commitment,other_parties,residence_since,property_magnitude,age,other_payment_plans,housing,existing_credits,job,num_dependents,own_telephone,foreign_worker,class
2
+ female,'<0',18,'existing paid',radio/tv,3190,'<100','1<=X<4',2,none,2,'real estate',24,none,own,1,skilled,1,none,yes,bad
3
+ male,'<0',18,'existing paid','new car',4380,'100<=X<500','1<=X<4',3,none,4,car,35,none,own,1,'unskilled resident',2,yes,yes,good
4
+ male,'<0',24,'all paid','new car',2325,'100<=X<500','4<=X<7',2,none,3,car,32,bank,own,1,skilled,1,none,yes,good
5
+ male,'>=200',12,'existing paid',radio/tv,1297,'<100','1<=X<4',3,none,4,'real estate',23,none,rent,1,skilled,1,none,yes,good
6
+ male,'no checking',33,'critical/other existing credit','used car',7253,'<100','4<=X<7',3,none,2,car,35,none,own,2,'high qualif/self emp/mgmt',1,yes,yes,good
7
+ male,'<0',24,'existing paid',radio/tv,2384,'<100','>=7',4,none,4,'real estate',64,bank,rent,1,'unskilled resident',1,none,yes,good
8
+ male,'>=200',6,'existing paid',furniture/equipment,2116,'<100','1<=X<4',2,none,2,'real estate',41,none,own,1,skilled,1,yes,yes,good
9
+ male,'0<=X<200',12,'delayed previously',radio/tv,585,'<100','1<=X<4',4,'co applicant',4,'real estate',20,none,rent,2,skilled,1,none,yes,good
10
+ male,'no checking',9,'existing paid','new car',3577,'100<=X<500','1<=X<4',1,guarantor,2,'real estate',26,none,rent,1,skilled,2,none,no,good
11
+ male,'no checking',27,'delayed previously','used car',8613,'>=1000','1<=X<4',2,none,2,car,27,none,own,2,skilled,1,none,yes,good
12
+ male,'0<=X<200',6,'existing paid',radio/tv,484,'<100','4<=X<7',3,guarantor,3,'real estate',28,bank,own,1,'unskilled resident',1,none,yes,good
13
+ male,'<0',42,'existing paid',radio/tv,3965,'<100','<1',4,none,3,car,34,none,own,1,skilled,1,none,yes,bad
14
+ female,'no checking',24,'existing paid',radio/tv,1376,'500<=X<1000','4<=X<7',4,none,1,car,28,none,own,1,skilled,1,none,yes,good
15
+ male,'<0',60,'existing paid',business,7297,'<100','>=7',4,'co applicant',4,'no known property',36,none,rent,1,skilled,1,none,yes,bad
16
+ male,'0<=X<200',60,'existing paid',education,6288,'<100','1<=X<4',4,none,4,'no known property',42,none,'for free',1,skilled,1,none,yes,bad
17
+ male,'<0',18,'existing paid',furniture/equipment,4153,'<100','1<=X<4',2,'co applicant',3,car,42,none,own,1,skilled,1,none,yes,bad
18
+ male,'no checking',15,'critical/other existing credit','used car',3368,'>=1000','>=7',3,none,4,'no known property',23,none,rent,2,skilled,1,yes,yes,good
19
+ female,'no checking',18,'critical/other existing credit',radio/tv,1098,'<100',unemployed,4,none,4,car,65,none,own,2,'unemp/unskilled non res',1,none,yes,good
20
+ female,'<0',18,'critical/other existing credit',furniture/equipment,2124,'<100','1<=X<4',4,none,4,'real estate',24,none,rent,2,skilled,1,none,yes,bad
21
+ female,'<0',15,'delayed previously',furniture/equipment,3643,'<100','>=7',1,none,4,'life insurance',27,none,own,2,'unskilled resident',1,none,yes,good
22
+ male,'no checking',48,'critical/other existing credit','used car',8858,'no known savings','4<=X<7',2,none,1,'no known property',35,none,'for free',2,skilled,1,yes,yes,good
23
+ male,'<0',21,'delayed previously',education,3414,'<100','<1',2,none,1,'life insurance',26,none,own,2,skilled,1,none,yes,bad
24
+ male,'no checking',18,'critical/other existing credit',radio/tv,6070,'<100','>=7',3,none,4,car,33,none,own,2,skilled,1,yes,yes,good
25
+ male,'no checking',4,'critical/other existing credit',radio/tv,1503,'<100','4<=X<7',2,none,1,'real estate',42,none,own,2,'unskilled resident',2,none,yes,good
26
+ male,'no checking',9,'critical/other existing credit',radio/tv,3074,'no known savings','1<=X<4',1,none,2,'real estate',33,none,own,2,skilled,2,none,yes,good
27
+ male,'<0',24,'existing paid',radio/tv,1823,'<100',unemployed,4,none,2,car,30,stores,own,1,'high qualif/self emp/mgmt',2,none,yes,bad
28
+ male,'0<=X<200',36,'existing paid',radio/tv,2323,'<100','4<=X<7',4,none,4,car,24,none,rent,1,skilled,1,none,yes,good
29
+ male,'>=200',42,'no credits/all paid',business,6289,'<100','<1',2,none,1,'life insurance',33,none,own,2,skilled,1,none,yes,good
30
+ male,'no checking',36,'critical/other existing credit','used car',10477,'no known savings','>=7',2,none,4,'no known property',42,none,'for free',2,skilled,1,none,yes,good
31
+ male,'no checking',12,'existing paid','new car',2859,'no known savings',unemployed,4,none,4,'no known property',38,none,own,1,'high qualif/self emp/mgmt',1,yes,yes,good
32
+ male,'0<=X<200',13,'critical/other existing credit',radio/tv,882,'<100','<1',4,guarantor,4,'real estate',23,none,own,2,skilled,1,none,yes,good
33
+ female,'>=200',12,'existing paid',radio/tv,1881,'<100','1<=X<4',2,none,2,car,44,none,rent,1,'unskilled resident',1,yes,yes,good
34
+ male,'no checking',18,'critical/other existing credit','new car',1530,'<100','1<=X<4',3,none,2,'life insurance',32,bank,own,2,skilled,1,none,yes,bad
35
+ male,'>=200',6,'critical/other existing credit','new car',1323,'100<=X<500','>=7',2,none,4,car,28,none,own,2,skilled,2,yes,yes,good
36
+ male,'no checking',36,'existing paid','new car',3079,'no known savings','1<=X<4',4,none,4,'real estate',36,none,own,1,skilled,1,none,yes,good
37
+ male,'0<=X<200',24,'existing paid','used car',2760,'no known savings','>=7',4,none,4,'no known property',36,bank,'for free',1,skilled,1,yes,yes,good
38
+ male,'0<=X<200',36,'delayed previously','new car',2862,'100<=X<500','>=7',4,none,3,'no known property',30,none,'for free',1,skilled,1,none,yes,good
39
+ female,'no checking',12,'existing paid','new car',2133,'no known savings','>=7',4,none,4,'no known property',52,none,'for free',1,'high qualif/self emp/mgmt',1,yes,yes,good
40
+ male,'no checking',20,'critical/other existing credit','new car',3485,'no known savings','<1',2,none,4,'real estate',44,none,own,2,skilled,1,yes,yes,good
41
+ female,'<0',36,'critical/other existing credit',furniture/equipment,6229,'<100','<1',4,'co applicant',4,'no known property',23,none,rent,2,'unskilled resident',1,yes,yes,bad
42
+ male,'>=200',36,'existing paid',radio/tv,4473,'<100','>=7',4,none,2,car,31,none,own,1,skilled,1,none,yes,good
43
+ female,'no checking',12,'critical/other existing credit',education,2012,'no known savings','4<=X<7',4,none,2,car,61,none,own,1,skilled,1,none,yes,good
44
+ female,'>=200',24,'existing paid',furniture/equipment,3749,'<100','<1',2,none,4,car,26,none,own,1,skilled,1,none,yes,good
45
+ female,'no checking',30,'critical/other existing credit',radio/tv,2831,'<100','1<=X<4',4,none,2,car,33,none,own,1,skilled,1,yes,yes,good
46
+ male,'0<=X<200',21,'critical/other existing credit',furniture/equipment,2745,'>=1000','4<=X<7',3,none,2,car,32,none,own,2,skilled,1,yes,yes,good
47
+ male,'<0',12,'existing paid',furniture/equipment,1262,'no known savings','>=7',2,none,4,'life insurance',49,none,own,1,'unskilled resident',1,yes,yes,good
48
+ male,'<0',24,'all paid',furniture/equipment,6872,'<100','<1',2,none,1,'life insurance',55,bank,own,1,skilled,1,yes,yes,bad
49
+ female,'0<=X<200',9,'existing paid',furniture/equipment,918,'<100','1<=X<4',4,none,1,'life insurance',30,none,own,1,skilled,1,none,yes,bad
50
+ female,'>=200',12,'all paid',business,609,'<100','<1',4,none,1,'real estate',26,none,own,1,'unemp/unskilled non res',1,none,yes,bad
51
+ female,'no checking',4,'existing paid',furniture/equipment,601,'<100','<1',1,none,3,'real estate',23,none,rent,1,'unskilled resident',2,none,yes,good
52
+ female,'<0',24,'existing paid',furniture/equipment,3234,'<100','<1',4,none,4,'real estate',23,none,rent,1,'unskilled resident',1,yes,yes,bad
53
+ male,'no checking',30,'critical/other existing credit',radio/tv,6742,'no known savings','4<=X<7',2,none,3,'life insurance',36,none,own,2,skilled,1,none,yes,good
54
+ female,'<0',24,'existing paid',radio/tv,1603,'<100','>=7',4,none,4,car,55,none,own,1,skilled,1,none,yes,good
55
+ male,'0<=X<200',36,'critical/other existing credit','new car',2820,'<100','<1',4,none,4,car,27,none,own,2,skilled,1,none,yes,bad
56
+ male,'0<=X<200',12,'critical/other existing credit','used car',1804,'100<=X<500','<1',3,none,4,'life insurance',44,none,own,1,skilled,1,none,yes,good
57
+ male,'0<=X<200',18,'existing paid',business,1913,'>=1000','<1',3,none,3,'real estate',36,bank,own,1,skilled,1,yes,yes,good
58
+ male,'<0',6,'critical/other existing credit','new car',3676,'<100','1<=X<4',1,none,3,'real estate',37,none,rent,3,skilled,2,none,yes,good
59
+ female,'0<=X<200',12,'existing paid','new car',1295,'<100','<1',3,none,1,car,25,none,rent,1,skilled,1,none,yes,bad
60
+ female,'<0',12,'existing paid',education,1200,'no known savings','1<=X<4',4,none,4,'life insurance',23,bank,rent,1,skilled,1,yes,yes,good
61
+ male,'no checking',12,'existing paid','new car',1101,'<100','1<=X<4',3,none,2,'real estate',27,none,own,2,skilled,1,yes,yes,good
62
+ female,'no checking',12,'existing paid','used car',4675,'no known savings','<1',1,none,4,car,20,none,rent,1,skilled,1,none,yes,good
63
+ male,'0<=X<200',36,'delayed previously','new car',2225,'<100','>=7',4,none,4,'no known property',57,bank,'for free',2,skilled,1,yes,yes,bad
64
+ male,'<0',30,'existing paid',furniture/equipment,6350,'no known savings','>=7',4,none,4,'life insurance',31,none,own,1,skilled,1,none,yes,bad
65
+ male,'no checking',12,'existing paid','used car',1413,'>=1000','4<=X<7',3,none,2,'life insurance',55,none,own,1,skilled,1,none,no,good
66
+ female,'>=200',10,'existing paid',furniture/equipment,1275,'<100','<1',4,none,2,'life insurance',23,none,own,1,skilled,1,none,yes,good
67
+ male,'0<=X<200',24,'existing paid',radio/tv,2896,'100<=X<500','<1',2,none,1,car,29,none,own,1,skilled,1,none,yes,good
68
+ male,'no checking',21,'existing paid',furniture/equipment,2241,'<100','>=7',4,none,2,'real estate',50,none,own,2,skilled,1,none,yes,good
69
+ female,'<0',18,'existing paid',radio/tv,2389,'<100','<1',4,none,1,car,27,stores,own,1,skilled,1,none,yes,good
70
+ female,'no checking',36,'existing paid','used car',8133,'<100','1<=X<4',1,none,2,'life insurance',30,bank,own,1,skilled,1,none,yes,good
71
+ male,'>=200',18,'existing paid',furniture/equipment,2864,'<100','1<=X<4',2,none,1,'real estate',34,none,own,1,'unskilled resident',2,none,yes,bad
72
+ male,'0<=X<200',12,'existing paid','new car',6078,'<100','4<=X<7',2,none,2,car,32,none,own,1,skilled,1,none,yes,good
73
+ male,'0<=X<200',6,'existing paid',radio/tv,368,'no known savings','>=7',4,none,4,'life insurance',38,none,own,1,skilled,1,none,yes,good
74
+ female,'<0',12,'critical/other existing credit',radio/tv,385,'<100','4<=X<7',4,none,3,'real estate',58,none,own,4,'unskilled resident',1,yes,yes,good
75
+ male,'0<=X<200',10,'all paid',radio/tv,1048,'<100','1<=X<4',4,none,4,'real estate',23,stores,own,1,'unskilled resident',1,none,yes,good
76
+ female,'<0',24,'critical/other existing credit','used car',6419,'<100','>=7',2,none,4,'no known property',44,none,'for free',2,'high qualif/self emp/mgmt',2,yes,yes,good
77
+ male,'<0',24,'delayed previously',radio/tv,1024,'<100','<1',4,none,4,'real estate',48,stores,own,1,skilled,1,none,yes,bad
78
+ male,'<0',24,'existing paid','new car',2303,'<100','>=7',4,'co applicant',1,'real estate',45,none,own,1,skilled,1,none,yes,bad
79
+ male,'0<=X<200',9,'existing paid',radio/tv,458,'<100','1<=X<4',4,none,3,'real estate',24,none,own,1,skilled,1,none,yes,good
80
+ male,'<0',12,'critical/other existing credit',furniture/equipment,2246,'<100','>=7',3,none,3,'life insurance',60,none,own,2,skilled,1,none,yes,bad
81
+ male,'<0',12,'existing paid',radio/tv,727,'100<=X<500','<1',4,none,3,'no known property',33,none,own,1,'unskilled resident',1,yes,yes,bad
82
+ female,'no checking',18,'existing paid',radio/tv,1453,'<100','<1',3,none,1,'real estate',26,none,own,1,skilled,1,none,yes,good
83
+ female,'no checking',12,'existing paid',radio/tv,2171,'<100','<1',2,none,2,car,29,bank,own,1,skilled,1,none,yes,good
84
+ male,'no checking',9,'existing paid',radio/tv,2697,'<100','1<=X<4',1,none,2,'real estate',32,none,own,1,skilled,2,none,yes,good
85
+ male,'0<=X<200',12,'existing paid','new car',1007,'>=1000','1<=X<4',4,none,1,'real estate',22,none,own,1,skilled,1,none,yes,good
86
+ male,'no checking',12,'critical/other existing credit',education,701,'<100','1<=X<4',4,none,2,car,32,none,own,2,skilled,1,none,yes,good
87
+ female,'<0',12,'all paid',radio/tv,626,'<100','1<=X<4',4,none,4,'real estate',24,bank,own,1,'unskilled resident',1,none,yes,bad
88
+ male,'<0',45,'existing paid',radio/tv,1845,'<100','1<=X<4',4,none,4,'no known property',23,none,'for free',1,skilled,1,yes,yes,bad
89
+ male,'0<=X<200',60,'existing paid','new car',14027,'<100','4<=X<7',4,none,2,'no known property',27,none,own,1,'high qualif/self emp/mgmt',1,yes,yes,bad
90
+ female,'no checking',30,'critical/other existing credit',radio/tv,5771,'<100','4<=X<7',4,none,2,car,25,none,own,2,skilled,1,none,yes,good
91
+ female,'no checking',24,'existing paid','new car',1525,'>=1000','4<=X<7',4,none,3,car,34,none,own,1,skilled,2,yes,yes,good
92
+ female,'no checking',22,'existing paid','new car',1283,'no known savings','4<=X<7',4,none,4,'life insurance',25,none,rent,1,skilled,1,none,yes,good
93
+ female,'no checking',6,'existing paid',radio/tv,518,'<100','1<=X<4',3,none,1,'real estate',29,none,own,1,skilled,1,none,yes,good
94
+ male,'<0',48,'no credits/all paid',furniture/equipment,7119,'<100','1<=X<4',3,none,4,'no known property',53,none,'for free',2,skilled,2,none,yes,bad
95
+ male,'<0',24,'existing paid',furniture/equipment,3021,'<100','1<=X<4',2,none,2,'real estate',24,none,rent,1,'unskilled resident',1,none,yes,good
96
+ male,'no checking',48,'critical/other existing credit','used car',2751,'no known savings','>=7',4,none,3,car,38,none,own,2,skilled,2,yes,yes,good
97
+ male,'no checking',6,'existing paid',repairs,660,'500<=X<1000','4<=X<7',2,none,4,'real estate',23,none,rent,1,'unskilled resident',1,none,yes,good
98
+ male,'no checking',24,'critical/other existing credit','new car',2463,'100<=X<500','4<=X<7',4,none,3,'life insurance',27,none,own,2,skilled,1,yes,yes,good
99
+ male,'<0',18,'existing paid','new car',2249,'100<=X<500','4<=X<7',4,none,3,car,30,none,own,1,'high qualif/self emp/mgmt',2,yes,yes,good
100
+ male,'0<=X<200',48,'no credits/all paid',business,14421,'<100','1<=X<4',2,none,2,car,25,none,own,1,skilled,1,yes,yes,bad
101
+ female,'<0',18,'critical/other existing credit','new car',3966,'<100','>=7',1,none,4,'real estate',33,bank,rent,3,skilled,1,yes,yes,bad
102
+ male,'no checking',30,'critical/other existing credit',radio/tv,3077,'no known savings','>=7',3,none,2,car,40,none,own,2,skilled,2,yes,yes,good
103
+ female,'0<=X<200',9,'existing paid',furniture/equipment,959,'<100','1<=X<4',1,none,2,car,29,none,own,1,skilled,1,none,no,bad
104
+ female,'>=200',9,'existing paid',radio/tv,745,'<100','1<=X<4',3,none,2,'real estate',28,none,own,1,'unskilled resident',1,none,yes,bad
105
+ male,'no checking',24,'critical/other existing credit',radio/tv,2684,'<100','1<=X<4',4,none,2,'real estate',35,none,own,2,'unskilled resident',1,none,yes,good
106
+ male,'no checking',12,'existing paid',education,1393,'<100','>=7',4,none,4,'life insurance',47,bank,own,3,skilled,2,yes,yes,good
107
+ male,'<0',18,'critical/other existing credit',radio/tv,1880,'<100','4<=X<7',4,none,1,'life insurance',32,none,own,2,'high qualif/self emp/mgmt',1,yes,yes,good
108
+ female,'0<=X<200',9,'existing paid',education,1199,'<100','4<=X<7',4,none,4,'life insurance',67,none,own,2,'high qualif/self emp/mgmt',1,yes,yes,good
109
+ male,'0<=X<200',24,'existing paid',furniture/equipment,3069,'100<=X<500','>=7',4,none,4,'no known property',30,none,'for free',1,skilled,1,none,yes,good
110
+ female,'no checking',24,'existing paid',furniture/equipment,3972,'<100','4<=X<7',2,none,4,'life insurance',25,none,rent,1,skilled,1,yes,yes,good
111
+ male,'<0',6,'existing paid','new car',14896,'<100','>=7',1,none,4,'no known property',68,bank,own,1,'high qualif/self emp/mgmt',1,yes,yes,bad
112
+ male,'<0',36,'existing paid',radio/tv,2302,'<100','1<=X<4',4,none,4,car,31,none,rent,1,skilled,1,none,yes,bad
113
+ male,'<0',8,'critical/other existing credit','new car',731,'<100','>=7',4,none,4,'real estate',47,none,own,2,'unskilled resident',1,none,yes,good
114
+ female,'<0',15,'critical/other existing credit',furniture/equipment,1433,'<100','1<=X<4',4,none,3,'life insurance',25,none,rent,2,skilled,1,none,yes,good
115
+ male,'no checking',6,'existing paid','domestic appliance',1338,'500<=X<1000','1<=X<4',1,none,4,'real estate',62,none,own,1,skilled,1,none,yes,good
116
+ female,'0<=X<200',18,'critical/other existing credit',furniture/equipment,1295,'<100','<1',4,none,1,'life insurance',27,none,own,2,skilled,1,none,yes,good
117
+ male,'<0',6,'critical/other existing credit',furniture/equipment,1872,'<100',unemployed,4,none,4,'no known property',36,none,'for free',3,'high qualif/self emp/mgmt',1,yes,yes,good
118
+ male,'0<=X<200',18,'critical/other existing credit','new car',884,'<100','>=7',4,none,4,car,36,bank,own,1,skilled,2,yes,yes,bad
119
+ male,'no checking',24,'delayed previously','new car',2538,'<100','>=7',4,none,4,car,47,none,own,2,'unskilled resident',2,none,yes,bad
120
+ male,'no checking',24,'existing paid',radio/tv,3105,'no known savings','<1',4,none,2,car,25,none,own,2,skilled,1,none,yes,good
121
+ male,'no checking',48,'critical/other existing credit',business,7629,'no known savings','>=7',4,none,2,car,46,bank,own,2,'high qualif/self emp/mgmt',2,none,yes,good
122
+ male,'<0',12,'critical/other existing credit','new car',2171,'<100','1<=X<4',4,none,4,'life insurance',38,bank,own,2,'unskilled resident',1,none,no,good
123
+ male,'0<=X<200',18,'existing paid','used car',2779,'<100','1<=X<4',1,none,3,car,21,none,rent,1,skilled,1,yes,yes,good
124
+ male,'<0',9,'critical/other existing credit',radio/tv,1138,'<100','1<=X<4',4,none,4,'real estate',25,none,own,2,'unskilled resident',1,none,yes,good
125
+ male,'<0',12,'existing paid',furniture/equipment,1657,'<100','1<=X<4',2,none,2,'real estate',27,none,own,1,skilled,1,none,yes,good
126
+ male,'0<=X<200',21,'existing paid',business,2767,'100<=X<500','>=7',4,none,2,car,61,bank,rent,2,'unskilled resident',1,none,yes,bad
127
+ male,'0<=X<200',18,'critical/other existing credit',furniture/equipment,1928,'<100','<1',2,none,2,'real estate',31,none,own,2,'unskilled resident',1,none,yes,bad
128
+ male,'0<=X<200',36,'existing paid',repairs,2384,'<100','<1',4,none,1,'no known property',33,none,rent,1,'unskilled resident',1,none,yes,bad
129
+ female,'no checking',9,'critical/other existing credit',education,1244,'no known savings','>=7',4,none,4,'life insurance',41,none,rent,2,'unskilled resident',1,none,yes,good
130
+ male,'no checking',12,'critical/other existing credit',furniture/equipment,3331,'<100','>=7',2,none,4,'life insurance',42,stores,own,1,skilled,1,none,yes,good
131
+ male,'no checking',24,'critical/other existing credit',education,1597,'<100','>=7',4,none,4,'no known property',54,none,'for free',2,skilled,2,none,yes,good
132
+ male,'no checking',24,'delayed previously',business,3863,'<100','1<=X<4',1,none,2,'no known property',32,none,'for free',1,skilled,1,none,yes,good
133
+ male,'<0',12,'existing paid',radio/tv,709,'<100','>=7',4,none,4,'real estate',57,stores,own,1,'unskilled resident',1,none,yes,bad
134
+ male,'0<=X<200',15,'existing paid',radio/tv,802,'<100','>=7',4,none,3,car,37,none,own,1,skilled,2,none,yes,bad
135
+ female,'no checking',12,'existing paid',furniture/equipment,1736,'<100','4<=X<7',3,none,4,'real estate',31,none,own,1,'unskilled resident',1,none,yes,good
136
+ male,'<0',6,'existing paid','new car',662,'<100','<1',3,none,4,'real estate',41,none,own,1,'unskilled resident',2,yes,yes,good
137
+ male,'no checking',6,'all paid','new car',783,'no known savings','1<=X<4',1,guarantor,2,'real estate',26,stores,own,1,'unskilled resident',2,none,yes,good
138
+ female,'<0',21,'existing paid',radio/tv,1835,'<100','1<=X<4',3,none,2,'real estate',25,none,own,2,skilled,1,yes,yes,bad
139
+ female,'0<=X<200',6,'critical/other existing credit',retraining,932,'no known savings','4<=X<7',1,none,3,'life insurance',39,none,own,2,'unskilled resident',1,none,yes,good
140
+ male,'<0',6,'existing paid',furniture/equipment,1374,'<100','1<=X<4',1,none,2,'real estate',36,bank,own,1,'unskilled resident',1,yes,yes,good
141
+ male,'<0',8,'critical/other existing credit',other,1164,'<100','>=7',3,none,4,'no known property',51,bank,'for free',2,'high qualif/self emp/mgmt',2,yes,yes,good
142
+ female,'<0',48,'critical/other existing credit','used car',6143,'<100','>=7',4,none,4,'no known property',58,stores,'for free',2,'unskilled resident',1,none,yes,bad
143
+ male,'no checking',6,'no credits/all paid','new car',1204,'100<=X<500','1<=X<4',4,none,1,'no known property',35,bank,rent,1,skilled,1,none,no,good
144
+ female,'0<=X<200',6,'all paid',education,433,'>=1000','<1',4,none,2,'life insurance',24,bank,rent,1,skilled,2,none,yes,bad
145
+ male,'no checking',12,'existing paid',furniture/equipment,1574,'<100','1<=X<4',4,none,2,'real estate',50,none,own,1,skilled,1,none,yes,good
146
+ male,'0<=X<200',36,'critical/other existing credit','used car',5800,'<100','1<=X<4',3,none,4,car,34,none,own,2,skilled,1,yes,yes,good
147
+ male,'<0',24,'all paid',business,3161,'<100','1<=X<4',4,none,2,'life insurance',31,none,rent,1,skilled,1,yes,yes,bad
148
+ male,'0<=X<200',8,'existing paid',business,907,'<100','<1',3,none,2,'real estate',26,none,own,1,skilled,1,yes,yes,good
149
+ female,'no checking',12,'all paid',retraining,3447,'500<=X<1000','1<=X<4',4,none,3,'real estate',35,none,own,1,'unskilled resident',2,none,yes,good
150
+ male,'<0',36,'existing paid',furniture/equipment,2712,'<100','>=7',2,none,2,'life insurance',41,bank,own,1,skilled,2,none,yes,bad
151
+ male,'<0',24,'existing paid',radio/tv,1938,'<100','<1',4,none,3,'life insurance',32,none,own,1,skilled,1,none,yes,bad
152
+ male,'no checking',24,'critical/other existing credit',radio/tv,1851,'<100','4<=X<7',4,guarantor,2,car,33,none,own,2,skilled,1,yes,yes,good
153
+ male,'0<=X<200',24,'existing paid','new car',3512,'100<=X<500','4<=X<7',2,none,3,car,38,bank,own,2,skilled,1,yes,yes,good
154
+ male,'0<=X<200',18,'delayed previously',business,2427,'no known savings','>=7',4,none,2,'life insurance',42,none,own,2,skilled,1,none,yes,good
155
+ female,'<0',18,'critical/other existing credit',repairs,1190,'<100',unemployed,2,none,4,'no known property',55,none,'for free',3,'unemp/unskilled non res',2,none,yes,bad
156
+ male,'no checking',10,'existing paid','new car',1546,'<100','1<=X<4',3,none,2,'real estate',31,none,own,1,'unskilled resident',2,none,no,good
157
+ female,'0<=X<200',12,'existing paid',furniture/equipment,3017,'<100','<1',3,none,1,'real estate',34,none,rent,1,'high qualif/self emp/mgmt',1,none,yes,good
158
+ male,'0<=X<200',9,'existing paid','new car',276,'<100','1<=X<4',4,none,4,'real estate',22,none,rent,1,'unskilled resident',1,none,yes,good
159
+ female,'no checking',12,'critical/other existing credit','new car',926,'<100',unemployed,1,none,2,'life insurance',38,none,own,1,'unemp/unskilled non res',1,none,yes,good
160
+ male,'0<=X<200',9,'existing paid',business,1391,'<100','1<=X<4',2,none,1,'real estate',27,bank,own,1,skilled,1,yes,yes,good
161
+ male,'0<=X<200',24,'existing paid',furniture/equipment,4057,'<100','4<=X<7',3,none,3,car,43,none,own,1,skilled,1,yes,yes,bad
162
+ female,'0<=X<200',6,'all paid','new car',931,'100<=X<500','<1',1,none,1,'life insurance',32,stores,own,1,'unskilled resident',1,none,yes,bad
163
+ female,'no checking',10,'existing paid','used car',2901,'no known savings','<1',1,none,4,'real estate',31,none,rent,1,skilled,1,none,yes,good
164
+ male,'<0',12,'existing paid',education,684,'<100','1<=X<4',4,none,4,car,40,none,rent,1,'unskilled resident',2,none,yes,bad
165
+ male,'<0',48,'existing paid',education,7476,'<100','4<=X<7',4,none,1,'no known property',50,none,'for free',1,'high qualif/self emp/mgmt',1,yes,yes,good
166
+ female,'no checking',15,'existing paid',furniture/equipment,2221,'500<=X<1000','1<=X<4',2,none,4,car,20,none,rent,1,skilled,1,none,yes,good
167
+ male,'<0',12,'critical/other existing credit','new car',4843,'<100','>=7',3,'co applicant',4,'life insurance',43,none,rent,2,skilled,1,yes,yes,bad
168
+ male,'no checking',18,'existing paid',furniture/equipment,2515,'<100','1<=X<4',3,none,4,'real estate',43,none,own,1,skilled,1,yes,yes,good
169
+ male,'<0',12,'existing paid','new car',3651,'>=1000','1<=X<4',1,none,3,'life insurance',31,none,own,1,skilled,2,none,yes,good
170
+ male,'>=200',4,'existing paid','new car',1494,'no known savings','<1',1,none,2,'real estate',29,none,own,1,'unskilled resident',2,none,no,good
171
+ male,'0<=X<200',48,'existing paid',other,5381,'no known savings',unemployed,3,none,4,'no known property',40,bank,'for free',1,'unemp/unskilled non res',1,yes,yes,good
172
+ male,'>=200',12,'existing paid',radio/tv,3399,'no known savings','>=7',2,none,3,car,37,none,own,1,'high qualif/self emp/mgmt',1,none,yes,good
173
+ male,'<0',15,'critical/other existing credit',furniture/equipment,1478,'<100','>=7',4,none,4,car,44,none,own,2,skilled,2,yes,yes,good
174
+ male,'0<=X<200',6,'delayed previously',business,1449,'100<=X<500','>=7',1,none,2,car,31,bank,own,2,skilled,2,none,yes,good
175
+ male,'0<=X<200',24,'critical/other existing credit',radio/tv,1743,'<100','>=7',4,none,2,'life insurance',48,none,own,2,'unskilled resident',1,none,yes,good
176
+ male,'no checking',12,'existing paid',radio/tv,3077,'<100','1<=X<4',2,none,4,car,52,none,own,1,skilled,1,yes,yes,good
177
+ male,'no checking',6,'existing paid',furniture/equipment,1766,'<100','1<=X<4',1,none,2,'life insurance',21,none,rent,1,skilled,1,none,yes,good
178
+ male,'0<=X<200',9,'existing paid',furniture/equipment,2030,'no known savings','4<=X<7',2,none,1,car,24,none,own,1,skilled,1,yes,yes,good
179
+ female,'no checking',11,'critical/other existing credit',radio/tv,1154,'100<=X<500',unemployed,4,none,4,'real estate',57,none,own,3,'unskilled resident',1,none,yes,good
180
+ female,'<0',20,'critical/other existing credit',furniture/equipment,4272,'<100','>=7',1,none,4,'life insurance',24,none,own,2,skilled,1,none,yes,good
181
+ male,'0<=X<200',72,'existing paid',radio/tv,5595,'100<=X<500','1<=X<4',2,none,2,car,24,none,own,1,skilled,1,none,yes,bad
182
+ male,'<0',12,'critical/other existing credit','new car',2122,'<100','1<=X<4',3,none,2,'real estate',39,none,rent,2,'unskilled resident',2,none,no,good
183
+ male,'no checking',24,'critical/other existing credit',business,4139,'100<=X<500','1<=X<4',3,none,3,'life insurance',27,none,own,2,'unskilled resident',1,yes,yes,good
184
+ male,'no checking',7,'delayed previously',radio/tv,846,'no known savings','>=7',3,none,4,'no known property',36,none,'for free',1,skilled,1,none,yes,good
185
+ female,'no checking',15,'critical/other existing credit',education,1532,'100<=X<500','1<=X<4',4,none,3,car,31,none,own,1,skilled,1,none,yes,good
186
+ male,'0<=X<200',21,'existing paid',furniture/equipment,3976,'no known savings','4<=X<7',2,none,3,car,35,none,own,1,skilled,1,yes,yes,good
187
+ male,'0<=X<200',12,'existing paid',radio/tv,766,'500<=X<1000','1<=X<4',4,none,3,'real estate',66,none,own,1,'unskilled resident',1,none,yes,bad
188
+ male,'0<=X<200',24,'existing paid','new car',1246,'<100','<1',4,none,2,'real estate',23,stores,own,1,'unskilled resident',1,none,yes,bad
189
+ male,'no checking',12,'existing paid',business,1542,'<100','4<=X<7',2,none,4,car,36,none,own,1,skilled,1,yes,yes,good
190
+ male,'no checking',24,'existing paid',furniture/equipment,929,'no known savings','4<=X<7',4,none,2,car,31,stores,own,1,skilled,1,yes,yes,good
191
+ male,'no checking',15,'existing paid','used car',3029,'<100','4<=X<7',2,none,2,car,33,none,own,1,skilled,1,none,yes,good
192
+ male,'no checking',18,'existing paid',furniture/equipment,1533,'<100','<1',4,'co applicant',1,'life insurance',43,none,own,1,'unskilled resident',2,none,yes,bad
193
+ male,'0<=X<200',48,'delayed previously',business,6681,'no known savings','1<=X<4',4,none,4,'no known property',38,none,'for free',1,skilled,2,yes,yes,good
194
+ male,'0<=X<200',12,'existing paid','new car',888,'<100','>=7',4,none,4,car,41,bank,own,1,'unskilled resident',2,none,yes,bad
195
+ male,'0<=X<200',18,'delayed previously',furniture/equipment,4297,'<100','>=7',4,none,3,'no known property',40,none,own,1,'high qualif/self emp/mgmt',1,yes,yes,bad
196
+ male,'>=200',30,'delayed previously',business,1908,'<100','>=7',4,none,4,'real estate',66,none,own,1,'high qualif/self emp/mgmt',1,yes,yes,bad
197
+ male,'no checking',24,'existing paid',radio/tv,3235,'500<=X<1000','>=7',3,none,2,car,26,none,own,1,'high qualif/self emp/mgmt',1,yes,yes,good
198
+ female,'0<=X<200',60,'existing paid','new car',7408,'100<=X<500','<1',4,none,2,'life insurance',24,none,own,1,'high qualif/self emp/mgmt',1,none,yes,bad
199
+ male,'<0',24,'existing paid',business,6568,'<100','1<=X<4',2,none,2,car,21,stores,own,1,'unskilled resident',1,none,yes,good
200
+ female,'<0',24,'all paid','used car',3632,'<100','1<=X<4',1,guarantor,4,car,22,bank,rent,1,skilled,1,none,no,good
201
+ male,'no checking',54,'no credits/all paid','used car',9436,'no known savings','1<=X<4',2,none,2,'life insurance',39,none,own,1,'unskilled resident',2,none,yes,good
test/ghana_test.csv ADDED
@@ -0,0 +1,292 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ sex,amnt req,ration,maturity,assets val,dec profit,xperience,educatn,age,collateral,locatn,guarantor,relatnshp,purpose,sector,savings,amnt grnt
2
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3
+ 0,4000,1,60.0,8000,200.0,5.0,2,32,7000,0,0,1,0,3,0,2000
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8
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10
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11
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12
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13
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14
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15
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16
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17
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18
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19
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24
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31
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32
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33
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35
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38
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39
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41
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42
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46
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52
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53
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54
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55
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56
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57
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58
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59
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60
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61
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62
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63
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64
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65
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66
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68
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69
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70
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82
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+ 1,5000,0,30.0,9000,700.0,7.0,1,27,1000,0,0,0,0,3,0,5000
170
+ 1,600,0,24.0,1500,310.0,5.0,1,28,10000,0,0,0,1,4,0,600
171
+ 0,3000,1,30.0,3500,350.0,4.0,2,38,3500,0,1,1,0,3,0,1000
172
+ 1,5000,1,60.0,4000,1200.0,5.0,1,40,3000,0,0,1,0,1,0,2000
173
+ 0,900,0,30.0,2000,135.0,5.0,2,31,4000,0,0,1,0,3,0,900
174
+ 0,2000,0,60.0,8000,1000.0,7.0,1,29,5000,0,0,1,1,1,0,2000
175
+ 1,1500,1,60.0,3600,470.0,16.0,3,45,2000,0,0,1,1,5,0,1500
176
+ 1,7000,1,30.0,30000,500.0,3.0,3,31,7000,0,0,0,1,5,0,5000
177
+ 1,500,1,30.0,5000,580.0,7.0,1,43,5000,0,0,0,1,1,0,450
178
+ 1,2000,1,30.0,2500,585.0,5.0,1,27,20000,1,0,0,1,4,0,1500
179
+ 0,15000,0,36.0,30000,5000.0,8.0,3,50,8000,0,1,1,1,3,1,15000
180
+ 1,2000,0,60.0,2000,700.0,1.0,3,37,3000,0,0,1,1,4,0,2000
181
+ 1,200,0,30.0,1000,300.0,2.0,3,34,1300,0,0,0,1,1,0,200
182
+ 1,5000,0,60.0,8400,1005.0,8.0,1,35,5000,1,0,0,0,1,0,5000
183
+ 1,1000,0,30.0,10000,540.0,3.0,1,39,4000,1,1,1,0,5,1,1000
184
+ 0,3000,0,36.0,4000,200.0,2.0,1,25,2230,1,1,1,1,4,0,3000
185
+ 1,1000,0,30.0,7000,800.0,5.0,1,34,3000,1,0,1,1,3,0,1000
186
+ 0,2500,1,36.0,39000,2400.0,2.0,1,36,4000,1,1,1,1,5,1,2400
187
+ 1,2000,0,30.0,3000,1100.0,3.0,1,40,1000,0,0,1,0,1,0,2000
188
+ 1,8000,0,60.0,2800,300.0,11.0,2,49,9000,1,0,0,0,2,0,8000
189
+ 0,500,1,30.0,1000,200.0,3.0,1,35,4000,0,0,0,1,2,0,400
190
+ 1,1600,0,60.0,2000,150.0,12.0,2,39,4000,1,0,1,0,3,0,1600
191
+ 1,1000,0,30.0,3000,100.0,3.0,1,36,4000,0,0,0,1,5,0,1000
192
+ 1,1000,0,30.0,5300,600.0,7.0,2,38,9000,1,0,1,1,5,0,1000
193
+ 1,2000,0,30.0,4000,400.0,0.0,1,37,3000,1,0,1,0,1,0,2000
194
+ 0,2000,1,40.0,3250,555.0,2.0,1,33,1500,1,0,0,1,1,0,1500
195
+ 1,2000,1,60.0,2600,793.0,1.0,1,39,1500,0,0,1,0,1,0,1800
196
+ 1,1500,0,30.0,3500,650.0,6.0,1,27,10000,0,0,1,1,4,0,1500
197
+ 0,10000,1,,9000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,8000
198
+ 0,1100,1,36.0,9000,920.0,2.0,3,25,920,1,1,0,0,5,1,1000
199
+ 0,3000,0,36.0,70000,4900.0,3.0,1,52,6000,0,1,0,0,1,1,3000
200
+ 1,3000,0,36.0,900,255.0,3.0,1,24,20000,0,0,1,1,5,0,3000
201
+ 0,10000,1,30.0,6000,250.0,3.0,2,35,9000,0,1,1,0,1,0,7000
202
+ 0,3000,0,30.0,4500,150.0,20.0,2,52,5000,0,0,1,1,3,0,3000
203
+ 0,20000,1,30.0,3600,280.0,5.0,2,30,12000,1,1,1,1,4,0,10000
204
+ 0,1200,0,30.0,2000,250.0,4.0,1,38,6000,1,0,0,0,1,0,1200
205
+ 1,1000,0,15.0,2500,459.0,5.0,1,36,12000,0,0,0,1,1,0,1000
206
+ 0,3000,0,36.0,12000,5000.0,6.0,2,26,5000,0,1,1,0,1,0,3000
207
+ 1,2000,0,30.0,2000,700.0,3.0,3,35,3000,0,0,1,0,4,0,2000
208
+ 1,1000,0,30.0,3000,100.0,4.0,1,29,4000,0,0,1,0,1,0,1000
209
+ 1,3000,0,30.0,6000,845.0,9.0,1,30,1500,0,0,1,0,1,0,3000
210
+ 0,2000,0,30.0,7000,600.0,5.0,1,32,6000,0,1,0,1,1,0,2000
211
+ 1,6000,0,60.0,8000,900.0,7.0,2,28,8500,1,1,1,1,3,0,6000
212
+ 1,1200,1,30.0,5000,600.0,10.0,1,32,5000,0,0,0,0,5,0,1000
213
+ 1,7000,1,60.0,900,190.0,1.0,2,43,4000,0,1,0,0,4,0,5000
214
+ 0,3000,0,60.0,10000,164.0,3.0,1,36,10000,0,0,0,0,1,0,3000
215
+ 1,1500,1,30.0,2000,300.0,4.0,1,41,4000,1,0,0,1,4,0,1000
216
+ 0,2500,0,60.0,2500,267.0,5.0,3,35,2000,1,0,0,0,5,0,1800
217
+ 1,600,0,36.0,1200,150.0,3.0,3,28,1000,0,0,1,0,1,0,600
218
+ 1,2000,0,30.0,6000,700.0,2.0,1,45,2000,0,0,1,0,1,0,2000
219
+ 1,600,0,15.0,1500,300.0,15.0,1,41,4000,0,0,1,1,5,0,600
220
+ 1,1000,0,30.0,8000,600.0,2.0,1,50,8000,0,0,0,0,1,0,1000
221
+ 1,10000,1,60.0,9000,600.0,4.0,4,49,9000,1,1,0,1,4,0,7000
222
+ 0,6000,1,30.0,6000,450.0,4.0,1,25,4050,0,1,1,0,1,0,4000
223
+ 0,6000,0,15.0,2400,300.0,4.0,1,42,1000,0,0,0,0,4,0,6000
224
+ 0,9000,0,30.0,10000,900.0,3.0,3,35,7000,1,0,0,1,4,1,9000
225
+ 1,8000,0,24.0,2800,300.0,11.0,2,49,9000,1,0,1,0,2,0,8000
226
+ 1,20000,1,30.0,10700,3000.0,4.0,2,38,13000,1,1,1,1,3,0,15000
227
+ 0,1040,0,30.0,1100,120.0,5.0,3,34,1800,0,0,1,1,5,0,1040
228
+ 0,3000,1,30.0,3500,655.0,5.0,1,26,15000,1,0,1,0,1,0,1500
229
+ 1,500,0,15.0,2400,540.0,8.0,3,36,2700,0,0,1,1,4,0,500
230
+ 1,15000,1,30.0,9000,3250.0,3.0,1,50,3250,0,1,0,0,1,0,7500
231
+ 1,2500,0,60.0,6500,660.0,5.0,3,58,3000,1,0,0,1,4,0,2500
232
+ 1,1200,0,30.0,9000,980.0,6.0,1,38,3000,0,0,1,1,4,0,1200
233
+ 1,1200,0,30.0,8000,1300.0,2.0,1,54,1300,0,1,1,0,1,0,1200
234
+ 0,2000,0,30.0,7000,100.0,6.0,2,36,4500,0,0,0,0,3,0,2000
235
+ 1,2500,0,30.0,9000,700.0,5.0,1,44,8000,1,0,0,0,1,0,2500
236
+ 1,2000,0,30.0,2500,700.0,2.0,3,31,2000,1,0,0,1,4,0,2000
237
+ 1,5000,0,30.0,3000,350.0,16.0,3,62,6000,0,0,0,0,4,0,5000
238
+ 0,10000,1,30.0,30000,500.0,3.0,3,31,10000,0,0,0,1,2,0,8000
239
+ 1,12000,1,30.0,7000,330.0,1.5,1,33,8000,0,1,0,0,4,0,8000
240
+ 1,3000,1,60.0,4030,708.0,10.0,1,57,1500,1,0,1,0,1,0,2000
241
+ 1,1000,0,30.0,2700,500.0,8.0,2,43,6200,1,0,1,1,4,0,1000
242
+ 1,500,0,30.0,2600,370.0,5.0,2,28,2700,0,0,1,0,5,0,500
243
+ 1,7000,1,60.0,900,190.0,1.0,2,43,4000,0,1,0,0,4,0,5000
244
+ 0,5000,0,60.0,12000,250.0,20.0,2,52,5000,0,0,1,1,3,0,5000
245
+ 0,1000,0,30.0,2400,368.0,3.0,3,34,2000,0,0,1,1,5,0,1000
246
+ 1,2500,0,60.0,2000,0.0,0.0,3,30,5000,0,0,0,0,3,0,2500
247
+ 0,1500,1,60.0,2900,650.0,4.0,3,40,2000,1,0,0,1,4,0,1300
248
+ 1,1500,0,30.0,3300,400.0,2.0,2,35,8000,0,0,0,0,1,0,1500
249
+ 1,500,0,15.0,1000,240.0,21.0,1,45,5000,0,0,0,1,5,0,500
250
+ 1,1500,0,50.0,1000,125.0,6.0,3,54,2000,1,0,1,1,4,0,1500
251
+ 0,2000,0,30.0,7000,1200.0,1.0,1,41,9000,0,1,1,1,3,1,2000
252
+ 1,2000,0,30.0,4000,810.0,4.0,1,28,10000,0,0,1,0,1,0,2000
253
+ 1,7000,1,60.0,900,190.0,1.0,2,43,4000,0,1,0,0,4,0,5000
254
+ 1,800,0,30.0,3400,600.0,6.0,2,30,5000,0,0,1,1,4,0,800
255
+ 0,1000,0,30.0,1800,185.0,3.0,1,38,1800,1,0,0,1,1,0,1000
256
+ 0,12000,1,60.0,20000,100.0,1.0,3,40,15000,1,1,1,1,4,0,10000
257
+ 1,2000,0,30.0,4500,450.0,9.0,2,32,1200,0,0,1,1,5,0,2000
258
+ 0,15000,1,36.0,6000,700.0,8.0,3,33,6000,0,0,0,1,4,0,10000
259
+ 0,5000,1,30.0,8000,500.0,2.0,1,29,1000,0,0,0,0,1,0,4000
260
+ 1,2000,1,60.0,8000,1200.0,2.0,1,43,2500,0,1,1,0,5,1,1500
261
+ 1,8000,1,60.0,6000,300.0,2.0,3,30,8000,0,1,0,0,5,0,5000
262
+ 1,400,0,30.0,3000,200.0,4.0,2,33,3000,0,0,0,0,1,0,400
263
+ 1,2500,0,60.0,10000,700.0,5.0,1,33,8000,0,0,1,1,5,0,2500
264
+ 1,7000,1,60.0,9000,500.0,1.0,2,43,8000,0,1,0,0,4,0,5000
265
+ 1,2000,0,60.0,2240,397.0,20.0,1,52,3000,0,0,1,0,1,0,1500
266
+ 0,10000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,8000
267
+ 1,30000,1,36.0,9000,900.0,11.0,2,36,9000,0,0,1,0,1,0,20000
268
+ 0,8000,1,60.0,6000,300.0,2.0,3,30,7000,0,1,0,0,5,0,5000
269
+ 0,1000,0,30.0,2000,360.0,5.0,1,44,2000,1,0,0,0,1,0,1000
270
+ 0,1000,0,30.0,3000,500.0,6.0,1,38,4000,0,0,1,1,5,0,1000
271
+ 1,1500,0,30.0,3200,768.0,5.0,1,32,15000,0,0,1,1,4,0,1500
272
+ 0,2500,1,30.0,4800,600.0,3.0,3,40,8000,0,1,1,1,5,0,2200
273
+ 1,800,0,20.0,1600,240.0,2.0,2,49,600,1,0,1,1,4,0,800
274
+ 0,1800,0,30.0,40000,2400.0,4.0,1,41,5000,1,1,0,1,5,1,1800
275
+ 0,1500,1,30.0,9000,1000.0,1.5,1,23,1000,0,1,1,0,1,0,1000
276
+ 0,1000,0,30.0,2000,260.0,7.0,1,38,2000,0,0,1,0,1,0,1000
277
+ 0,5000,0,60.0,20000,7000.0,4.0,1,44,7000,0,1,1,1,3,1,5000
278
+ 1,7000,1,60.0,900,190.0,1.0,2,43,4000,0,1,0,0,4,0,5000
279
+ 1,4000,0,60.0,8000,800.0,7.0,3,48,6000,0,0,0,0,5,0,4000
280
+ 0,9000,1,,9000,700.0,3.0,3,55,9000,1,0,1,1,3,0,8000
281
+ 0,8000,0,15.0,600,4500.0,5.0,1,30,10000,0,1,1,0,2,0,8000
282
+ 0,20000,0,60.0,50000,2500.0,8.0,3,49,7000,1,1,0,0,3,1,20000
283
+ 0,2000,1,15.0,7000,500.0,5.0,2,36,1500,0,1,1,1,5,0,1000
284
+ 1,1000,0,15.0,4000,150.0,7.0,3,28,1500,0,1,1,0,1,1,1000
285
+ 1,5000,1,60.0,5000,2000.0,2.5,1,45,3000,0,0,0,1,1,0,2000
286
+ 0,1000,0,20.0,2000,300.0,2.0,1,41,1200,0,0,1,0,1,0,1000
287
+ 1,1000,0,30.0,2300,500.0,8.0,2,36,6000,0,0,0,1,1,0,1000
288
+ 1,800,0,20.0,1600,300.0,4.0,1,34,8000,0,0,1,0,1,0,800
289
+ 1,1000,1,36.0,1600,200.0,2.0,1,51,7000,0,0,1,0,1,0,800
290
+ 0,1000,0,30.0,5000,500.0,1.0,3,23,4000,0,0,0,1,5,0,1000
291
+ 1,4000,0,60.0,8000,1550.0,11.0,1,34,3000,0,0,1,0,1,0,4000
292
+ 1,1500,1,30.0,2000,300.0,1.0,1,53,1500,0,0,1,1,4,0,1000
test/loanpred_test.csv ADDED
@@ -0,0 +1,124 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Gender,Loan_ID,Gender,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_Status
2
+ Male,LP002139,Male,Yes,0,Graduate,No,9083,0.0,228.0,360.0,1.0,Semiurban,Y
3
+ Male,LP002223,Male,Yes,0,Graduate,No,4310,0.0,130.0,360.0,,Semiurban,Y
4
+ Male,LP001570,Male,Yes,2,Graduate,No,4167,1447.0,158.0,360.0,1.0,Rural,Y
5
+ Female,LP002978,Female,No,0,Graduate,No,2900,0.0,71.0,360.0,1.0,Rural,Y
6
+ Male,LP001478,Male,No,0,Graduate,No,2718,0.0,70.0,360.0,1.0,Semiurban,Y
7
+ Male,LP002877,Male,Yes,1,Graduate,No,1782,2232.0,107.0,360.0,1.0,Rural,Y
8
+ Male,LP002035,Male,Yes,2,Graduate,No,3717,0.0,120.0,360.0,1.0,Semiurban,Y
9
+ Male,LP001005,Male,Yes,0,Graduate,Yes,3000,0.0,66.0,360.0,1.0,Urban,Y
10
+ Male,LP002115,Male,Yes,3+,Not Graduate,No,2647,1587.0,173.0,360.0,1.0,Rural,N
11
+ Male,LP001259,Male,Yes,1,Graduate,Yes,1000,3022.0,110.0,360.0,1.0,Urban,N
12
+ Male,LP001732,Male,Yes,2,Graduate,,5000,0.0,72.0,360.0,0.0,Semiurban,N
13
+ Male,LP002487,Male,Yes,0,Graduate,No,3015,2188.0,153.0,360.0,1.0,Rural,Y
14
+ Male,LP001384,Male,Yes,3+,Not Graduate,No,2071,754.0,94.0,480.0,1.0,Semiurban,Y
15
+ Male,LP002054,Male,Yes,2,Not Graduate,No,3601,1590.0,,360.0,1.0,Rural,Y
16
+ Male,LP001491,Male,Yes,2,Graduate,Yes,3316,3500.0,88.0,360.0,1.0,Urban,Y
17
+ Male,LP002178,Male,Yes,0,Graduate,No,3013,3033.0,95.0,300.0,,Urban,Y
18
+ Male,LP001699,Male,No,0,Graduate,No,2479,0.0,59.0,360.0,1.0,Urban,Y
19
+ Male,LP001349,Male,No,0,Graduate,No,4843,3806.0,151.0,360.0,1.0,Semiurban,Y
20
+ Male,LP001778,Male,Yes,1,Graduate,No,3155,1779.0,140.0,360.0,1.0,Semiurban,Y
21
+ Male,LP001636,Male,Yes,0,Graduate,No,4600,0.0,73.0,180.0,1.0,Semiurban,Y
22
+ Male,LP002401,Male,Yes,0,Graduate,No,2213,1125.0,,360.0,1.0,Urban,Y
23
+ Male,LP002170,Male,Yes,2,Graduate,No,5000,3667.0,236.0,360.0,1.0,Semiurban,Y
24
+ Male,LP001760,Male,,,Graduate,No,4758,0.0,158.0,480.0,1.0,Semiurban,Y
25
+ Male,LP001953,Male,Yes,1,Graduate,No,6875,0.0,200.0,360.0,1.0,Semiurban,Y
26
+ Female,LP002634,Female,No,1,Graduate,No,13262,0.0,40.0,360.0,1.0,Urban,Y
27
+ Male,LP001666,Male,No,0,Graduate,No,8333,3750.0,187.0,360.0,1.0,Rural,Y
28
+ Male,LP002544,Male,Yes,1,Not Graduate,No,1958,2436.0,131.0,360.0,1.0,Rural,Y
29
+ Male,LP001702,Male,No,0,Graduate,No,3418,0.0,127.0,360.0,1.0,Semiurban,N
30
+ Female,LP002144,Female,No,,Graduate,No,3813,0.0,116.0,180.0,1.0,Urban,Y
31
+ Male,LP002979,Male,Yes,3+,Graduate,No,4106,0.0,40.0,180.0,1.0,Rural,Y
32
+ Male,LP001024,Male,Yes,2,Graduate,No,3200,700.0,70.0,360.0,1.0,Urban,Y
33
+ Female,LP001514,Female,Yes,0,Graduate,No,2330,4486.0,100.0,360.0,1.0,Semiurban,Y
34
+ Male,LP001972,Male,Yes,,Not Graduate,No,2875,1750.0,105.0,360.0,1.0,Semiurban,Y
35
+ Male,LP002874,Male,No,0,Graduate,No,3229,2739.0,110.0,360.0,1.0,Urban,Y
36
+ Female,LP001519,Female,No,0,Graduate,No,10000,1666.0,225.0,360.0,1.0,Rural,N
37
+ Male,LP002328,Male,Yes,0,Not Graduate,No,6096,0.0,218.0,360.0,0.0,Rural,N
38
+ Male,LP002467,Male,Yes,0,Graduate,No,3708,2569.0,173.0,360.0,1.0,Urban,N
39
+ Male,LP002953,Male,Yes,3+,Graduate,No,5703,0.0,128.0,360.0,1.0,Urban,Y
40
+ Male,LP001194,Male,Yes,2,Graduate,No,2708,1167.0,97.0,360.0,1.0,Semiurban,Y
41
+ Female,LP001267,Female,Yes,2,Graduate,No,1378,1881.0,167.0,360.0,1.0,Urban,N
42
+ Male,LP001385,Male,No,0,Graduate,No,5316,0.0,136.0,360.0,1.0,Urban,Y
43
+ Male,LP002755,Male,Yes,1,Not Graduate,No,2239,2524.0,128.0,360.0,1.0,Urban,Y
44
+ Male,LP002050,Male,Yes,1,Graduate,Yes,10000,0.0,155.0,360.0,1.0,Rural,N
45
+ Male,LP002777,Male,Yes,0,Graduate,No,2785,2016.0,110.0,360.0,1.0,Rural,Y
46
+ Male,LP001473,Male,No,0,Graduate,No,2014,1929.0,74.0,360.0,1.0,Urban,Y
47
+ Male,LP001691,Male,Yes,2,Not Graduate,No,3917,0.0,124.0,360.0,1.0,Semiurban,Y
48
+ Male,LP001091,Male,Yes,1,Graduate,,4166,3369.0,201.0,360.0,,Urban,N
49
+ Male,LP002841,Male,Yes,0,Graduate,No,3166,2064.0,104.0,360.0,0.0,Urban,N
50
+ Male,LP002448,Male,Yes,0,Graduate,No,3948,1733.0,149.0,360.0,0.0,Rural,N
51
+ Female,LP002776,Female,No,0,Graduate,No,5000,0.0,103.0,360.0,0.0,Semiurban,N
52
+ Male,LP002444,Male,No,1,Not Graduate,Yes,2769,1542.0,190.0,360.0,,Semiurban,N
53
+ Female,LP001708,Female,No,0,Graduate,No,10000,0.0,214.0,360.0,1.0,Semiurban,N
54
+ Male,LP001964,Male,Yes,0,Not Graduate,No,1800,2934.0,93.0,360.0,0.0,Urban,N
55
+ Female,LP002684,Female,No,0,Not Graduate,No,3400,0.0,95.0,360.0,1.0,Rural,N
56
+ Male,LP001243,Male,Yes,0,Graduate,No,3208,3066.0,172.0,360.0,1.0,Urban,Y
57
+ Male,LP001532,Male,Yes,2,Not Graduate,No,2281,0.0,113.0,360.0,1.0,Rural,N
58
+ Male,LP001256,Male,No,0,Graduate,No,3750,4750.0,176.0,360.0,1.0,Urban,N
59
+ Male,LP001713,Male,Yes,1,Graduate,Yes,7787,0.0,240.0,360.0,1.0,Urban,Y
60
+ Male,LP002911,Male,Yes,1,Graduate,No,2787,1917.0,146.0,360.0,0.0,Rural,N
61
+ Male,LP002892,Male,Yes,2,Graduate,No,6540,0.0,205.0,360.0,1.0,Semiurban,Y
62
+ Male,LP001536,Male,Yes,3+,Graduate,No,39999,0.0,600.0,180.0,0.0,Semiurban,Y
63
+ Male,LP001052,Male,Yes,1,Graduate,,3717,2925.0,151.0,360.0,,Semiurban,N
64
+ Male,LP002778,Male,Yes,2,Graduate,Yes,6633,0.0,,360.0,0.0,Rural,N
65
+ Female,LP002407,Female,Yes,0,Not Graduate,Yes,7142,0.0,138.0,360.0,1.0,Rural,Y
66
+ Male,LP002266,Male,Yes,2,Graduate,No,3100,1400.0,113.0,360.0,1.0,Urban,Y
67
+ Female,LP002231,Female,No,0,Graduate,No,6000,0.0,156.0,360.0,1.0,Urban,Y
68
+ Female,LP001087,Female,No,2,Graduate,,3750,2083.0,120.0,360.0,1.0,Semiurban,Y
69
+ Male,LP002531,Male,Yes,1,Graduate,Yes,16667,2250.0,86.0,360.0,1.0,Semiurban,Y
70
+ Male,LP001854,Male,Yes,3+,Graduate,No,5250,0.0,94.0,360.0,1.0,Urban,N
71
+ Male,LP001657,Male,Yes,0,Not Graduate,No,6033,0.0,160.0,360.0,1.0,Urban,N
72
+ Female,LP002357,Female,No,0,Not Graduate,No,2720,0.0,80.0,,0.0,Urban,N
73
+ Male,LP001904,Male,Yes,0,Graduate,No,3103,1300.0,80.0,360.0,1.0,Urban,Y
74
+ Male,LP001603,Male,Yes,0,Not Graduate,Yes,4344,736.0,87.0,360.0,1.0,Semiurban,N
75
+ Male,LP001497,Male,Yes,2,Graduate,No,5042,2083.0,185.0,360.0,1.0,Rural,N
76
+ Male,LP001263,Male,Yes,3+,Graduate,No,3167,4000.0,180.0,300.0,0.0,Semiurban,N
77
+ Male,LP001266,Male,Yes,1,Graduate,Yes,2395,0.0,,360.0,1.0,Semiurban,Y
78
+ Male,LP002622,Male,Yes,2,Graduate,No,3510,4416.0,243.0,360.0,1.0,Rural,Y
79
+ Male,LP001213,Male,Yes,1,Graduate,No,4945,0.0,,360.0,0.0,Rural,N
80
+ Female,LP002277,Female,No,0,Graduate,No,3180,0.0,71.0,360.0,0.0,Urban,N
81
+ Male,LP001248,Male,No,0,Graduate,No,3500,0.0,81.0,300.0,1.0,Semiurban,Y
82
+ Male,LP002505,Male,Yes,0,Graduate,No,4333,2451.0,110.0,360.0,1.0,Urban,N
83
+ Male,LP002868,Male,Yes,2,Graduate,No,3159,461.0,108.0,84.0,1.0,Urban,Y
84
+ Male,LP002863,Male,Yes,3+,Graduate,No,6406,0.0,150.0,360.0,1.0,Semiurban,N
85
+ Female,LP002840,Female,No,0,Graduate,No,2378,0.0,9.0,360.0,1.0,Urban,N
86
+ Male,LP001357,Male,,,Graduate,No,3816,754.0,160.0,360.0,1.0,Urban,Y
87
+ Male,LP002082,Male,Yes,0,Graduate,Yes,5818,2160.0,184.0,360.0,1.0,Semiurban,Y
88
+ Male,LP002842,Male,Yes,1,Graduate,No,3417,1750.0,186.0,360.0,1.0,Urban,Y
89
+ Male,LP002926,Male,Yes,2,Graduate,Yes,2726,0.0,106.0,360.0,0.0,Semiurban,N
90
+ Male,LP001013,Male,Yes,0,Not Graduate,No,2333,1516.0,95.0,360.0,1.0,Urban,Y
91
+ Male,LP001922,Male,Yes,0,Graduate,No,20667,0.0,,360.0,1.0,Rural,N
92
+ Male,LP001488,Male,Yes,3+,Graduate,No,4000,7750.0,290.0,360.0,1.0,Semiurban,N
93
+ Male,LP002379,Male,No,0,Graduate,No,6500,0.0,105.0,360.0,0.0,Rural,N
94
+ Male,LP001835,Male,Yes,0,Not Graduate,No,1668,3890.0,201.0,360.0,0.0,Semiurban,N
95
+ Male,LP002190,Male,Yes,1,Graduate,No,6325,0.0,175.0,360.0,1.0,Semiurban,Y
96
+ Male,LP002798,Male,Yes,0,Graduate,No,3887,2669.0,162.0,360.0,1.0,Semiurban,Y
97
+ Male,LP001608,Male,Yes,2,Graduate,No,2045,1619.0,101.0,360.0,1.0,Rural,Y
98
+ Female,LP002522,Female,No,0,Graduate,Yes,2500,0.0,93.0,360.0,,Urban,Y
99
+ Male,LP001280,Male,Yes,2,Not Graduate,No,3333,2000.0,99.0,360.0,,Semiurban,Y
100
+ Male,LP001634,Male,No,0,Graduate,No,1916,5063.0,67.0,360.0,,Rural,N
101
+ Male,LP001546,Male,No,0,Graduate,,2980,2083.0,120.0,360.0,1.0,Rural,Y
102
+ Male,LP001914,Male,Yes,0,Graduate,No,3927,800.0,112.0,360.0,1.0,Semiurban,Y
103
+ Male,LP001900,Male,Yes,1,Graduate,No,2750,1842.0,115.0,360.0,1.0,Semiurban,Y
104
+ Male,LP002940,Male,No,0,Not Graduate,No,3833,0.0,110.0,360.0,1.0,Rural,Y
105
+ ,LP001644,,Yes,0,Graduate,Yes,674,5296.0,168.0,360.0,1.0,Rural,Y
106
+ Male,LP001865,Male,Yes,1,Graduate,No,6083,4250.0,330.0,360.0,,Urban,Y
107
+ Male,LP002446,Male,Yes,2,Not Graduate,No,2309,1255.0,125.0,360.0,0.0,Rural,N
108
+ Male,LP002366,Male,Yes,0,Graduate,No,2666,4300.0,121.0,360.0,1.0,Rural,Y
109
+ Male,LP001250,Male,Yes,3+,Not Graduate,No,4755,0.0,95.0,,0.0,Semiurban,N
110
+ Male,LP001116,Male,No,0,Not Graduate,No,3748,1668.0,110.0,360.0,1.0,Semiurban,Y
111
+ Female,LP002337,Female,No,0,Graduate,No,2995,0.0,60.0,360.0,1.0,Urban,Y
112
+ Female,LP001790,Female,No,1,Graduate,No,3812,0.0,112.0,360.0,1.0,Rural,Y
113
+ Male,LP001228,Male,No,0,Not Graduate,No,3200,2254.0,126.0,180.0,0.0,Urban,N
114
+ Male,LP001926,Male,Yes,0,Graduate,No,3704,2000.0,120.0,360.0,1.0,Rural,Y
115
+ Male,LP001784,Male,Yes,1,Graduate,No,5500,1260.0,170.0,360.0,1.0,Rural,Y
116
+ Male,LP001123,Male,Yes,0,Graduate,No,2400,0.0,75.0,360.0,,Urban,Y
117
+ Male,LP002284,Male,No,0,Not Graduate,No,3902,1666.0,109.0,360.0,1.0,Rural,Y
118
+ Male,LP001205,Male,Yes,0,Graduate,No,2500,3796.0,120.0,360.0,1.0,Urban,Y
119
+ Male,LP001421,Male,Yes,0,Graduate,No,5568,2142.0,175.0,360.0,1.0,Rural,N
120
+ Male,LP001768,Male,Yes,0,Graduate,,3716,0.0,42.0,180.0,1.0,Rural,Y
121
+ Female,LP002006,Female,No,0,Graduate,No,2507,0.0,56.0,360.0,1.0,Rural,Y
122
+ Male,LP001824,Male,Yes,1,Graduate,No,2882,1843.0,123.0,480.0,1.0,Semiurban,Y
123
+ Male,LP001027,Male,Yes,2,Graduate,,2500,1840.0,109.0,360.0,1.0,Urban,Y
124
+ Male,LP002101,Male,Yes,0,Graduate,,63337,0.0,490.0,180.0,1.0,Urban,Y
test/modifiedghana_test.csv ADDED
@@ -0,0 +1,292 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ sex,amnt req,amnt grnt,ration,maturity,assets val,dec profit,xperience,educatn,age,collateral,locatn,guarantor,relatnshp,purpose,sector,savings,target
2
+ 0,2500,2500,0,30.0,8500,700.0,26.0,2,55,5000,1,0,1,0,5,0,Yes
3
+ 0,4000,2000,1,60.0,8000,200.0,5.0,2,32,7000,0,0,1,0,3,0,No
4
+ 1,3000,3000,0,30.0,2130,327.0,6.0,1,32,1500,0,0,0,0,1,0,Yes
5
+ 0,9000,9000,0,,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,Yes
6
+ 1,2000,2000,0,30.0,8000,500.0,6.0,1,45,500,1,0,0,0,1,0,Yes
7
+ 0,6000,6000,0,36.0,32000,10000.0,6.0,3,48,9000,0,1,1,0,1,1,Yes
8
+ 0,400,400,0,30.0,1095,400.0,2.0,2,33,10000,0,0,0,0,1,0,Yes
9
+ 0,4000,3000,1,30.0,5000,300.0,6.0,2,40,5000,0,0,0,1,5,0,No
10
+ 0,9000,9000,0,30.0,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,Yes
11
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
12
+ 1,7000,7000,0,60.0,10000,120.0,4.0,2,34,20000,0,0,1,0,3,0,Yes
13
+ 0,10000,3500,1,30.0,1200,120.0,2.5,2,27,5000,0,1,1,0,3,0,No
14
+ 0,1000,700,1,30.0,10000,300.0,3.0,1,47,1500,0,1,1,1,5,1,No
15
+ 1,7000,7000,0,60.0,10000,120.0,4.0,2,34,20000,1,0,1,0,3,0,Yes
16
+ 1,1200,1200,0,36.0,3000,500.0,5.0,1,40,1000,1,0,1,1,4,0,Yes
17
+ 1,5000,4000,1,30.0,1500,500.0,3.0,1,47,4500,1,0,1,1,5,0,No
18
+ 0,9000,6000,1,30.0,8000,800.0,2.0,4,33,8000,0,0,1,0,4,1,No
19
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
20
+ 0,3000,3000,0,30.0,10000,900.0,5.0,3,42,3000,1,0,0,0,5,0,Yes
21
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
22
+ 1,8000,6000,1,30.0,5000,600.0,2.0,1,33,2000,0,1,0,0,3,0,No
23
+ 1,3000,3000,0,60.0,3590,517.0,8.0,1,28,1500,0,0,1,0,1,0,Yes
24
+ 1,20000,20000,0,30.0,17000,8000.0,6.0,3,53,9000,1,1,0,0,3,1,Yes
25
+ 0,1000,500,1,30.0,40000,400.0,1.0,1,34,2500,0,1,1,0,4,1,No
26
+ 1,4000,2000,1,36.0,5000,550.0,6.0,1,20,250,0,0,0,0,1,0,No
27
+ 1,1500,1500,0,30.0,3500,358.0,5.0,1,41,3000,0,0,1,0,1,0,Yes
28
+ 1,800,500,0,15.0,3200,530.0,7.0,2,35,3000,0,0,0,0,1,0,No
29
+ 0,1000,1000,0,30.0,2500,700.0,1.0,3,28,10000,0,0,0,0,1,0,Yes
30
+ 1,2000,2000,0,30.0,4000,300.0,4.0,1,36,5000,0,0,1,0,1,0,Yes
31
+ 1,2000,2000,0,30.0,2280,612.0,5.0,1,40,1500,1,0,1,0,1,0,Yes
32
+ 0,1000,1000,0,15.0,3000,200.0,12.0,3,45,6000,1,1,1,1,5,0,Yes
33
+ 1,600,600,0,30.0,5000,480.0,1.0,1,29,2000,0,1,0,0,5,1,Yes
34
+ 0,8000,5000,1,60.0,5000,400.0,1.0,2,30,7000,1,0,0,1,4,0,No
35
+ 1,7000,5000,1,,5000,650.0,3.0,3,47,6000,1,1,1,0,4,0,No
36
+ 0,1000,1000,0,30.0,2500,500.0,4.0,1,39,4500,0,0,1,1,2,0,Yes
37
+ 0,9000,9000,0,30.0,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,Yes
38
+ 1,800,500,1,60.0,1500,250.0,25.0,1,50,1500,1,1,0,0,1,0,No
39
+ 0,2200,1500,1,30.0,2500,250.0,4.0,1,52,6000,0,0,0,1,1,0,No
40
+ 1,5000,5000,0,30.0,3000,350.0,16.0,3,62,6000,0,0,0,0,4,0,Yes
41
+ 0,3000,2500,1,60.0,3830,530.0,4.0,1,48,1500,0,0,1,0,1,0,No
42
+ 0,8000,8000,0,60.0,6000,250.0,5.0,1,30,9000,0,1,1,0,2,0,Yes
43
+ 1,7000,5000,1,60.0,900,190.0,1.0,2,43,4000,0,1,0,0,4,0,No
44
+ 0,2500,2500,0,30.0,4000,375.0,2.0,2,34,4500,0,0,1,0,3,0,Yes
45
+ 0,30000,30000,0,36.0,250000,25000.0,3.0,1,43,6000,0,1,1,1,3,1,Yes
46
+ 0,3000,3000,0,40.0,3500,450.0,24.0,1,48,4000,0,0,0,0,5,0,Yes
47
+ 1,300,300,0,60.0,2580,650.0,3.0,1,41,5000,0,0,1,1,1,0,Yes
48
+ 0,2000,2000,0,30.0,3500,356.0,4.0,3,40,3000,1,0,0,1,4,0,Yes
49
+ 0,600,600,0,60.0,6300,500.0,5.0,3,46,2000,0,0,1,1,4,0,Yes
50
+ 0,5000,5000,0,30.0,4000,200.0,3.0,3,30,5000,1,0,1,1,5,0,Yes
51
+ 1,10000,7000,1,,9000,600.0,4.0,4,49,9000,1,1,0,1,4,0,No
52
+ 0,3000,2000,1,30.0,1000,200.0,6.0,3,35,4500,0,0,1,0,4,0,No
53
+ 1,1000,1000,0,30.0,1000,300.0,1.0,1,34,5000,0,0,1,1,1,0,Yes
54
+ 1,600,500,1,60.0,14000,1000.0,1.0,1,25,6000,1,1,0,0,1,0,No
55
+ 0,2000,2000,0,12.0,4000,450.0,7.0,1,42,6000,0,0,0,0,1,0,Yes
56
+ 0,3000,3000,0,30.0,4000,470.0,5.0,3,38,6000,1,0,1,1,5,0,Yes
57
+ 0,5000,2500,1,30.0,6000,350.0,6.0,1,31,1500,1,0,0,1,1,0,No
58
+ 0,2000,2000,0,30.0,4000,800.0,2.0,1,36,10000,1,1,1,0,1,1,Yes
59
+ 0,4300,4300,0,60.0,8000,450.0,5.0,1,58,6500,1,0,0,0,2,0,Yes
60
+ 0,2000,2000,0,30.0,4000,200.0,3.0,1,40,4000,0,0,1,1,1,0,Yes
61
+ 0,700,700,0,30.0,1500,350.0,4.0,2,40,1000,0,0,0,0,3,0,Yes
62
+ 1,800,800,0,30.0,1500,154.0,5.0,1,40,3000,1,0,0,0,1,0,Yes
63
+ 1,10000,7000,1,60.0,9000,600.0,4.0,4,49,9000,1,1,0,1,4,0,No
64
+ 0,1000,1000,0,60.0,30000,600.0,4.0,1,40,4000,0,1,1,1,5,1,Yes
65
+ 0,3500,3500,0,30.0,8000,925.0,6.0,1,27,5000,1,0,0,1,1,0,Yes
66
+ 1,1000,1000,0,30.0,4700,400.0,2.0,2,28,6000,0,0,1,1,5,0,Yes
67
+ 0,5000,3000,1,60.0,4500,1700.0,4.0,2,37,5000,0,0,1,0,2,0,No
68
+ 1,1000,1000,0,30.0,5200,500.0,4.0,3,32,2000,0,0,1,1,5,0,Yes
69
+ 1,4000,3000,1,60.0,6800,700.0,9.0,2,35,1800,0,0,0,1,4,0,No
70
+ 0,9000,6000,1,30.0,20000,4900.0,2.0,3,45,8000,0,1,0,1,3,1,No
71
+ 0,10000,8000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,No
72
+ 1,3000,1000,1,36.0,3000,880.0,4.5,1,38,2000,0,0,1,0,1,0,No
73
+ 0,10000,3500,1,30.0,4000,290.0,4.0,2,30,2900,0,1,1,1,4,0,No
74
+ 1,300,300,0,60.0,4200,300.0,0.0,2,20,1000,0,0,1,0,1,0,Yes
75
+ 1,600,600,0,30.0,1000,230.0,1.0,1,29,4500,0,0,1,0,1,0,Yes
76
+ 1,500,500,0,60.0,3400,650.0,6.0,3,37,3200,0,0,1,1,1,0,Yes
77
+ 0,5000,4600,1,60.0,60000,7000.0,3.0,1,49,8000,1,1,0,1,5,1,No
78
+ 0,800,800,0,30.0,3000,200.0,2.0,3,30,800,0,0,0,1,5,0,Yes
79
+ 0,2000,1800,1,60.0,1050,706.0,2.0,1,36,1500,0,0,1,1,1,0,No
80
+ 1,700,600,1,60.0,3000,500.0,31.0,1,56,3000,1,1,0,0,1,0,No
81
+ 0,5000,5000,0,30.0,8000,900.0,5.0,1,37,1200,1,0,1,0,2,0,Yes
82
+ 1,300,300,0,30.0,1625,200.0,5.0,2,31,6000,0,0,1,0,1,0,Yes
83
+ 0,10000,8000,1,30.0,4000,400.0,8.0,4,60,6000,1,0,1,1,4,1,No
84
+ 1,9000,6000,1,60.0,9000,1200.0,8.0,3,40,7000,1,1,0,1,4,0,No
85
+ 0,7000,6500,1,60.0,40000,3000.0,4.0,3,49,8000,0,1,1,0,1,1,No
86
+ 1,500,500,0,60.0,1000,200.0,15.0,1,40,1000,0,1,1,0,1,0,Yes
87
+ 0,1600,1600,0,60.0,5000,285.0,3.0,3,25,4000,0,0,1,1,4,0,Yes
88
+ 1,800,800,0,30.0,1000,400.0,30.0,2,56,1000,0,0,1,1,1,0,Yes
89
+ 1,4000,4000,0,,3250,400.0,9.0,2,44,5000,1,1,1,1,4,0,Yes
90
+ 0,9000,8000,1,12.0,9000,700.0,3.0,3,55,9000,1,0,1,1,3,0,No
91
+ 1,15000,15000,0,30.0,3600,2000.0,1.0,2,40,20000,0,1,1,0,5,0,Yes
92
+ 0,500,500,0,30.0,2300,500.0,4.0,1,39,2600,1,0,0,0,1,0,Yes
93
+ 1,7000,5000,1,60.0,12000,3000.0,6.0,3,41,9000,0,1,0,0,3,1,No
94
+ 1,2000,2000,0,30.0,5000,429.0,6.0,1,22,3000,0,0,1,1,1,0,Yes
95
+ 1,7000,7000,1,60.0,9000,356.0,6.0,1,57,8000,0,0,0,0,2,0,Yes
96
+ 0,1500,1400,1,30.0,3000,540.0,2.0,3,42,3000,1,1,0,1,1,1,No
97
+ 1,3000,1000,1,30.0,2000,600.0,5.0,1,32,1200,1,0,1,0,1,0,No
98
+ 0,10000,8000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,No
99
+ 1,2000,2000,0,90.0,7000,730.0,6.0,2,47,4000,0,1,0,0,3,0,Yes
100
+ 1,2000,2000,0,30.0,3000,680.0,1.0,3,35,4000,0,0,1,1,4,0,Yes
101
+ 1,1000,1000,0,50.0,1000,500.0,2.0,3,27,1000,0,0,1,1,5,0,Yes
102
+ 0,3000,3000,0,60.0,3830,600.0,5.0,1,33,5000,0,1,0,1,1,0,Yes
103
+ 0,1000,1000,0,30.0,4000,330.0,13.0,1,41,1500,0,1,0,0,1,0,Yes
104
+ 1,1200,1000,1,24.0,3500,512.0,6.0,1,35,20000,1,0,0,0,1,0,No
105
+ 0,10000,7000,1,30.0,9000,1000.0,2.0,1,25,1000,0,1,1,1,5,0,No
106
+ 0,10000,7000,1,30.0,4000,400.0,8.0,4,60,9000,1,0,1,1,4,1,No
107
+ 0,2500,2500,0,30.0,1500,160.0,3.0,1,39,3000,1,0,0,1,1,0,Yes
108
+ 0,1500,1200,1,50.0,3500,255.0,12.0,2,32,4100,0,0,0,0,3,0,No
109
+ 0,3000,3000,1,60.0,10000,256.0,2.0,1,48,5000,1,0,0,0,2,0,Yes
110
+ 1,5000,5000,0,30.0,8000,2300.0,3.0,1,30,4000,1,0,0,1,5,0,Yes
111
+ 1,3000,1000,1,60.0,2000,720.0,4.0,2,34,2000,0,0,1,1,4,0,No
112
+ 0,7500,7500,0,60.0,14000,165.0,5.0,3,45,10000,0,0,1,1,4,0,Yes
113
+ 0,5000,4000,1,30.0,8000,400.0,6.0,2,43,7000,0,0,0,1,3,0,No
114
+ 1,4000,4000,0,60.0,10000,200.0,6.0,1,34,10000,0,0,1,1,1,0,Yes
115
+ 1,1200,1200,0,36.0,7000,700.0,5.0,1,27,5000,1,0,0,0,2,0,Yes
116
+ 0,8000,5000,1,30.0,12000,500.0,20.0,2,52,7000,0,0,0,0,3,0,No
117
+ 0,1500,1500,0,60.0,2900,650.0,3.0,3,40,2000,1,0,0,1,4,0,Yes
118
+ 1,10000,1500,1,36.0,8000,3000.0,12.0,3,51,3000,0,0,1,1,5,1,No
119
+ 1,2000,2000,0,50.0,3000,200.0,4.0,2,29,3000,0,0,0,0,1,0,Yes
120
+ 1,1200,1200,0,30.0,7000,700.0,5.0,1,29,5000,1,0,1,1,5,0,Yes
121
+ 1,6000,6000,0,60.0,9500,900.0,7.0,2,28,9000,1,1,1,1,3,0,Yes
122
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
123
+ 1,2000,2000,0,60.0,2500,730.0,1.0,3,34,5000,1,0,0,0,1,0,Yes
124
+ 1,2000,1500,1,36.0,3700,400.0,28.0,2,48,2000,1,0,0,0,1,0,No
125
+ 0,3000,3000,0,30.0,4000,200.0,3.0,3,30,15000,0,0,1,1,5,0,Yes
126
+ 0,700,700,0,30.0,850,150.0,10.0,2,33,850,0,0,1,0,1,0,Yes
127
+ 0,9000,9000,0,30.0,3000,320.0,9.0,4,38,10000,1,1,1,1,1,1,Yes
128
+ 1,400,400,0,60.0,6800,700.0,2.0,3,43,2000,1,0,1,1,4,0,Yes
129
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
130
+ 1,5000,2000,1,60.0,4500,1400.0,4.0,1,38,3000,1,0,1,1,5,0,No
131
+ 0,8000,4000,1,30.0,8000,900.0,4.0,1,42,2900,0,1,1,0,1,0,No
132
+ 0,2000,2000,0,36.0,6000,125.0,3.0,1,30,3000,1,0,1,0,1,0,Yes
133
+ 0,20000,10000,1,30.0,7000,2800.0,5.0,2,44,2800,0,1,1,0,1,0,No
134
+ 0,500,500,0,30.0,1000,66.0,2.0,1,26,10000,0,0,1,0,1,0,Yes
135
+ 0,3000,3000,0,15.0,3900,500.0,5.0,2,40,2000,1,0,1,0,1,0,Yes
136
+ 1,2000,2000,0,60.0,4100,530.0,4.0,1,40,1500,0,1,1,1,1,0,Yes
137
+ 0,3000,2000,1,30.0,3800,725.0,2.0,1,26,15000,0,0,0,0,1,0,No
138
+ 1,1000,1000,0,50.0,2000,800.0,4.0,1,35,10000,0,0,0,0,1,0,Yes
139
+ 0,5000,5000,0,30.0,800,500.0,5.0,3,39,5000,1,0,1,0,3,0,Yes
140
+ 1,2500,2500,0,60.0,4000,560.0,3.0,1,32,8500,0,0,0,1,1,0,Yes
141
+ 0,8000,5000,1,60.0,5000,300.0,1.0,1,39,5000,0,0,1,0,2,0,No
142
+ 0,10000,5000,1,30.0,7000,540.0,1.5,3,30,5000,1,0,0,0,4,0,No
143
+ 1,6000,6000,0,15.0,6100,400.0,7.0,2,42,4000,0,0,1,1,4,0,Yes
144
+ 0,3000,2000,1,35.0,3000,700.0,4.0,2,28,3000,0,0,1,1,5,0,No
145
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
146
+ 0,300,300,0,60.0,2600,200.0,19.0,2,56,1700,0,0,1,1,4,0,Yes
147
+ 1,1000,1000,0,30.0,2000,630.0,1.0,3,33,2000,0,0,1,1,4,0,Yes
148
+ 1,4000,1000,1,12.0,7000,800.0,1.0,3,45,3000,0,0,0,1,4,0,No
149
+ 0,8000,5000,1,60.0,5000,4000.0,1.0,2,30,8000,1,0,0,1,4,0,No
150
+ 1,7000,5000,1,60.0,5000,650.0,3.0,3,47,6000,1,1,1,0,4,0,No
151
+ 1,1200,1200,0,60.0,7000,700.0,5.0,1,34,5000,1,0,1,1,5,0,Yes
152
+ 1,1600,1600,1,60.0,5000,150.0,5.0,3,25,4000,0,0,0,1,4,0,Yes
153
+ 0,10000,8000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,No
154
+ 0,20000,15000,1,36.0,5000,500.0,25.0,3,50,5000,1,0,0,0,4,0,No
155
+ 1,2000,2000,0,30.0,2000,820.0,1.0,3,30,5000,0,0,1,1,4,0,Yes
156
+ 1,7000,5000,1,60.0,7000,2100.0,3.5,1,46,9000,0,0,0,1,5,0,No
157
+ 1,1000,1000,0,36.0,8000,800.0,5.0,1,43,3000,1,0,0,1,5,0,Yes
158
+ 1,600,600,0,30.0,650,108.0,5.0,1,34,1500,0,0,0,1,1,0,Yes
159
+ 0,7000,6500,1,60.0,20000,4600.0,2.0,1,41,7000,0,1,1,0,1,1,No
160
+ 0,4300,4300,0,60.0,8000,450.0,5.0,1,58,6500,1,0,0,0,2,0,Yes
161
+ 0,1200,1200,0,30.0,2000,600.0,3.0,1,40,2000,0,0,0,1,5,0,Yes
162
+ 1,8000,8000,0,,2800,300.0,11.0,2,49,9000,1,0,1,0,2,0,Yes
163
+ 1,800,800,0,15.0,1500,500.0,2.0,1,32,4500,0,0,1,1,1,0,Yes
164
+ 1,20000,12000,1,30.0,11000,117.0,1.5,3,39,8000,1,1,1,1,4,0,No
165
+ 0,3000,3000,0,60.0,5000,245.0,3.0,1,42,5000,1,0,0,0,2,0,Yes
166
+ 0,10000,7000,1,30.0,4000,400.0,8.0,4,60,9000,0,0,1,1,4,1,No
167
+ 0,1200,1000,1,30.0,3500,568.0,10.0,1,43,4000,0,0,1,0,1,0,No
168
+ 0,500,400,1,30.0,4000,480.0,5.0,1,57,6000,0,0,1,1,1,0,No
169
+ 1,5000,5000,0,30.0,9000,700.0,7.0,1,27,1000,0,0,0,0,3,0,Yes
170
+ 1,600,600,0,24.0,1500,310.0,5.0,1,28,10000,0,0,0,1,4,0,Yes
171
+ 0,3000,1000,1,30.0,3500,350.0,4.0,2,38,3500,0,1,1,0,3,0,No
172
+ 1,5000,2000,1,60.0,4000,1200.0,5.0,1,40,3000,0,0,1,0,1,0,No
173
+ 0,900,900,0,30.0,2000,135.0,5.0,2,31,4000,0,0,1,0,3,0,Yes
174
+ 0,2000,2000,0,60.0,8000,1000.0,7.0,1,29,5000,0,0,1,1,1,0,Yes
175
+ 1,1500,1500,1,60.0,3600,470.0,16.0,3,45,2000,0,0,1,1,5,0,Yes
176
+ 1,7000,5000,1,30.0,30000,500.0,3.0,3,31,7000,0,0,0,1,5,0,No
177
+ 1,500,450,1,30.0,5000,580.0,7.0,1,43,5000,0,0,0,1,1,0,No
178
+ 1,2000,1500,1,30.0,2500,585.0,5.0,1,27,20000,1,0,0,1,4,0,No
179
+ 0,15000,15000,0,36.0,30000,5000.0,8.0,3,50,8000,0,1,1,1,3,1,Yes
180
+ 1,2000,2000,0,60.0,2000,700.0,1.0,3,37,3000,0,0,1,1,4,0,Yes
181
+ 1,200,200,0,30.0,1000,300.0,2.0,3,34,1300,0,0,0,1,1,0,Yes
182
+ 1,5000,5000,0,60.0,8400,1005.0,8.0,1,35,5000,1,0,0,0,1,0,Yes
183
+ 1,1000,1000,0,30.0,10000,540.0,3.0,1,39,4000,1,1,1,0,5,1,Yes
184
+ 0,3000,3000,0,36.0,4000,200.0,2.0,1,25,2230,1,1,1,1,4,0,Yes
185
+ 1,1000,1000,0,30.0,7000,800.0,5.0,1,34,3000,1,0,1,1,3,0,Yes
186
+ 0,2500,2400,1,36.0,39000,2400.0,2.0,1,36,4000,1,1,1,1,5,1,No
187
+ 1,2000,2000,0,30.0,3000,1100.0,3.0,1,40,1000,0,0,1,0,1,0,Yes
188
+ 1,8000,8000,0,60.0,2800,300.0,11.0,2,49,9000,1,0,0,0,2,0,Yes
189
+ 0,500,400,1,30.0,1000,200.0,3.0,1,35,4000,0,0,0,1,2,0,No
190
+ 1,1600,1600,0,60.0,2000,150.0,12.0,2,39,4000,1,0,1,0,3,0,Yes
191
+ 1,1000,1000,0,30.0,3000,100.0,3.0,1,36,4000,0,0,0,1,5,0,Yes
192
+ 1,1000,1000,0,30.0,5300,600.0,7.0,2,38,9000,1,0,1,1,5,0,Yes
193
+ 1,2000,2000,0,30.0,4000,400.0,0.0,1,37,3000,1,0,1,0,1,0,Yes
194
+ 0,2000,1500,1,40.0,3250,555.0,2.0,1,33,1500,1,0,0,1,1,0,No
195
+ 1,2000,1800,1,60.0,2600,793.0,1.0,1,39,1500,0,0,1,0,1,0,No
196
+ 1,1500,1500,0,30.0,3500,650.0,6.0,1,27,10000,0,0,1,1,4,0,Yes
197
+ 0,10000,8000,1,,9000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,No
198
+ 0,1100,1000,1,36.0,9000,920.0,2.0,3,25,920,1,1,0,0,5,1,No
199
+ 0,3000,3000,0,36.0,70000,4900.0,3.0,1,52,6000,0,1,0,0,1,1,Yes
200
+ 1,3000,3000,0,36.0,900,255.0,3.0,1,24,20000,0,0,1,1,5,0,Yes
201
+ 0,10000,7000,1,30.0,6000,250.0,3.0,2,35,9000,0,1,1,0,1,0,No
202
+ 0,3000,3000,0,30.0,4500,150.0,20.0,2,52,5000,0,0,1,1,3,0,Yes
203
+ 0,20000,10000,1,30.0,3600,280.0,5.0,2,30,12000,1,1,1,1,4,0,No
204
+ 0,1200,1200,0,30.0,2000,250.0,4.0,1,38,6000,1,0,0,0,1,0,Yes
205
+ 1,1000,1000,0,15.0,2500,459.0,5.0,1,36,12000,0,0,0,1,1,0,Yes
206
+ 0,3000,3000,0,36.0,12000,5000.0,6.0,2,26,5000,0,1,1,0,1,0,Yes
207
+ 1,2000,2000,0,30.0,2000,700.0,3.0,3,35,3000,0,0,1,0,4,0,Yes
208
+ 1,1000,1000,0,30.0,3000,100.0,4.0,1,29,4000,0,0,1,0,1,0,Yes
209
+ 1,3000,3000,0,30.0,6000,845.0,9.0,1,30,1500,0,0,1,0,1,0,Yes
210
+ 0,2000,2000,0,30.0,7000,600.0,5.0,1,32,6000,0,1,0,1,1,0,Yes
211
+ 1,6000,6000,0,60.0,8000,900.0,7.0,2,28,8500,1,1,1,1,3,0,Yes
212
+ 1,1200,1000,1,30.0,5000,600.0,10.0,1,32,5000,0,0,0,0,5,0,No
213
+ 1,7000,5000,1,60.0,900,190.0,1.0,2,43,4000,0,1,0,0,4,0,No
214
+ 0,3000,3000,0,60.0,10000,164.0,3.0,1,36,10000,0,0,0,0,1,0,Yes
215
+ 1,1500,1000,1,30.0,2000,300.0,4.0,1,41,4000,1,0,0,1,4,0,No
216
+ 0,2500,1800,0,60.0,2500,267.0,5.0,3,35,2000,1,0,0,0,5,0,No
217
+ 1,600,600,0,36.0,1200,150.0,3.0,3,28,1000,0,0,1,0,1,0,Yes
218
+ 1,2000,2000,0,30.0,6000,700.0,2.0,1,45,2000,0,0,1,0,1,0,Yes
219
+ 1,600,600,0,15.0,1500,300.0,15.0,1,41,4000,0,0,1,1,5,0,Yes
220
+ 1,1000,1000,0,30.0,8000,600.0,2.0,1,50,8000,0,0,0,0,1,0,Yes
221
+ 1,10000,7000,1,60.0,9000,600.0,4.0,4,49,9000,1,1,0,1,4,0,No
222
+ 0,6000,4000,1,30.0,6000,450.0,4.0,1,25,4050,0,1,1,0,1,0,No
223
+ 0,6000,6000,0,15.0,2400,300.0,4.0,1,42,1000,0,0,0,0,4,0,Yes
224
+ 0,9000,9000,0,30.0,10000,900.0,3.0,3,35,7000,1,0,0,1,4,1,Yes
225
+ 1,8000,8000,0,24.0,2800,300.0,11.0,2,49,9000,1,0,1,0,2,0,Yes
226
+ 1,20000,15000,1,30.0,10700,3000.0,4.0,2,38,13000,1,1,1,1,3,0,No
227
+ 0,1040,1040,0,30.0,1100,120.0,5.0,3,34,1800,0,0,1,1,5,0,Yes
228
+ 0,3000,1500,1,30.0,3500,655.0,5.0,1,26,15000,1,0,1,0,1,0,No
229
+ 1,500,500,0,15.0,2400,540.0,8.0,3,36,2700,0,0,1,1,4,0,Yes
230
+ 1,15000,7500,1,30.0,9000,3250.0,3.0,1,50,3250,0,1,0,0,1,0,No
231
+ 1,2500,2500,0,60.0,6500,660.0,5.0,3,58,3000,1,0,0,1,4,0,Yes
232
+ 1,1200,1200,0,30.0,9000,980.0,6.0,1,38,3000,0,0,1,1,4,0,Yes
233
+ 1,1200,1200,0,30.0,8000,1300.0,2.0,1,54,1300,0,1,1,0,1,0,Yes
234
+ 0,2000,2000,0,30.0,7000,100.0,6.0,2,36,4500,0,0,0,0,3,0,Yes
235
+ 1,2500,2500,0,30.0,9000,700.0,5.0,1,44,8000,1,0,0,0,1,0,Yes
236
+ 1,2000,2000,0,30.0,2500,700.0,2.0,3,31,2000,1,0,0,1,4,0,Yes
237
+ 1,5000,5000,0,30.0,3000,350.0,16.0,3,62,6000,0,0,0,0,4,0,Yes
238
+ 0,10000,8000,1,30.0,30000,500.0,3.0,3,31,10000,0,0,0,1,2,0,No
239
+ 1,12000,8000,1,30.0,7000,330.0,1.5,1,33,8000,0,1,0,0,4,0,No
240
+ 1,3000,2000,1,60.0,4030,708.0,10.0,1,57,1500,1,0,1,0,1,0,No
241
+ 1,1000,1000,0,30.0,2700,500.0,8.0,2,43,6200,1,0,1,1,4,0,Yes
242
+ 1,500,500,0,30.0,2600,370.0,5.0,2,28,2700,0,0,1,0,5,0,Yes
243
+ 1,7000,5000,1,60.0,900,190.0,1.0,2,43,4000,0,1,0,0,4,0,No
244
+ 0,5000,5000,0,60.0,12000,250.0,20.0,2,52,5000,0,0,1,1,3,0,Yes
245
+ 0,1000,1000,0,30.0,2400,368.0,3.0,3,34,2000,0,0,1,1,5,0,Yes
246
+ 1,2500,2500,0,60.0,2000,0.0,0.0,3,30,5000,0,0,0,0,3,0,Yes
247
+ 0,1500,1300,1,60.0,2900,650.0,4.0,3,40,2000,1,0,0,1,4,0,No
248
+ 1,1500,1500,0,30.0,3300,400.0,2.0,2,35,8000,0,0,0,0,1,0,Yes
249
+ 1,500,500,0,15.0,1000,240.0,21.0,1,45,5000,0,0,0,1,5,0,Yes
250
+ 1,1500,1500,0,50.0,1000,125.0,6.0,3,54,2000,1,0,1,1,4,0,Yes
251
+ 0,2000,2000,0,30.0,7000,1200.0,1.0,1,41,9000,0,1,1,1,3,1,Yes
252
+ 1,2000,2000,0,30.0,4000,810.0,4.0,1,28,10000,0,0,1,0,1,0,Yes
253
+ 1,7000,5000,1,60.0,900,190.0,1.0,2,43,4000,0,1,0,0,4,0,No
254
+ 1,800,800,0,30.0,3400,600.0,6.0,2,30,5000,0,0,1,1,4,0,Yes
255
+ 0,1000,1000,0,30.0,1800,185.0,3.0,1,38,1800,1,0,0,1,1,0,Yes
256
+ 0,12000,10000,1,60.0,20000,100.0,1.0,3,40,15000,1,1,1,1,4,0,No
257
+ 1,2000,2000,0,30.0,4500,450.0,9.0,2,32,1200,0,0,1,1,5,0,Yes
258
+ 0,15000,10000,1,36.0,6000,700.0,8.0,3,33,6000,0,0,0,1,4,0,No
259
+ 0,5000,4000,1,30.0,8000,500.0,2.0,1,29,1000,0,0,0,0,1,0,No
260
+ 1,2000,1500,1,60.0,8000,1200.0,2.0,1,43,2500,0,1,1,0,5,1,No
261
+ 1,8000,5000,1,60.0,6000,300.0,2.0,3,30,8000,0,1,0,0,5,0,No
262
+ 1,400,400,0,30.0,3000,200.0,4.0,2,33,3000,0,0,0,0,1,0,Yes
263
+ 1,2500,2500,0,60.0,10000,700.0,5.0,1,33,8000,0,0,1,1,5,0,Yes
264
+ 1,7000,5000,1,60.0,9000,500.0,1.0,2,43,8000,0,1,0,0,4,0,No
265
+ 1,2000,1500,0,60.0,2240,397.0,20.0,1,52,3000,0,0,1,0,1,0,No
266
+ 0,10000,8000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,No
267
+ 1,30000,20000,1,36.0,9000,900.0,11.0,2,36,9000,0,0,1,0,1,0,No
268
+ 0,8000,5000,1,60.0,6000,300.0,2.0,3,30,7000,0,1,0,0,5,0,No
269
+ 0,1000,1000,0,30.0,2000,360.0,5.0,1,44,2000,1,0,0,0,1,0,Yes
270
+ 0,1000,1000,0,30.0,3000,500.0,6.0,1,38,4000,0,0,1,1,5,0,Yes
271
+ 1,1500,1500,0,30.0,3200,768.0,5.0,1,32,15000,0,0,1,1,4,0,Yes
272
+ 0,2500,2200,1,30.0,4800,600.0,3.0,3,40,8000,0,1,1,1,5,0,No
273
+ 1,800,800,0,20.0,1600,240.0,2.0,2,49,600,1,0,1,1,4,0,Yes
274
+ 0,1800,1800,0,30.0,40000,2400.0,4.0,1,41,5000,1,1,0,1,5,1,Yes
275
+ 0,1500,1000,1,30.0,9000,1000.0,1.5,1,23,1000,0,1,1,0,1,0,No
276
+ 0,1000,1000,0,30.0,2000,260.0,7.0,1,38,2000,0,0,1,0,1,0,Yes
277
+ 0,5000,5000,0,60.0,20000,7000.0,4.0,1,44,7000,0,1,1,1,3,1,Yes
278
+ 1,7000,5000,1,60.0,900,190.0,1.0,2,43,4000,0,1,0,0,4,0,No
279
+ 1,4000,4000,0,60.0,8000,800.0,7.0,3,48,6000,0,0,0,0,5,0,Yes
280
+ 0,9000,8000,1,,9000,700.0,3.0,3,55,9000,1,0,1,1,3,0,No
281
+ 0,8000,8000,0,15.0,600,4500.0,5.0,1,30,10000,0,1,1,0,2,0,Yes
282
+ 0,20000,20000,0,60.0,50000,2500.0,8.0,3,49,7000,1,1,0,0,3,1,Yes
283
+ 0,2000,1000,1,15.0,7000,500.0,5.0,2,36,1500,0,1,1,1,5,0,No
284
+ 1,1000,1000,0,15.0,4000,150.0,7.0,3,28,1500,0,1,1,0,1,1,Yes
285
+ 1,5000,2000,1,60.0,5000,2000.0,2.5,1,45,3000,0,0,0,1,1,0,No
286
+ 0,1000,1000,0,20.0,2000,300.0,2.0,1,41,1200,0,0,1,0,1,0,Yes
287
+ 1,1000,1000,0,30.0,2300,500.0,8.0,2,36,6000,0,0,0,1,1,0,Yes
288
+ 1,800,800,0,20.0,1600,300.0,4.0,1,34,8000,0,0,1,0,1,0,Yes
289
+ 1,1000,800,1,36.0,1600,200.0,2.0,1,51,7000,0,0,1,0,1,0,No
290
+ 0,1000,1000,0,30.0,5000,500.0,1.0,3,23,4000,0,0,0,1,5,0,Yes
291
+ 1,4000,4000,0,60.0,8000,1550.0,11.0,1,34,3000,0,0,1,0,1,0,Yes
292
+ 1,1500,1000,1,30.0,2000,300.0,1.0,1,53,1500,0,0,1,1,4,0,No
train/german_train.csv ADDED
The diff for this file is too large to render. See raw diff
 
train/ghana_train.csv ADDED
@@ -0,0 +1,1161 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ sex,amnt req,ration,maturity,assets val,dec profit,xperience,educatn,age,collateral,locatn,guarantor,relatnshp,purpose,sector,savings,amnt grnt
2
+ 0,2000,0,36.0,4000,500.0,3.0,1,28,900,0,0,1,0,1,0,2000
3
+ 1,1000,0,30.0,3000,600.0,6.0,2,35,3000,0,0,0,1,1,0,1000
4
+ 0,5000,1,40.0,7000,1350.0,5.0,3,35,2000,0,0,1,1,4,0,3000
5
+ 0,1000,0,24.0,2500,590.0,6.0,1,25,20000,1,0,1,0,1,0,1000
6
+ 1,2000,0,60.0,2800,320.0,12.0,3,42,2000,0,0,0,1,5,0,2000
7
+ 0,9000,0,30.0,5000,320.0,9.0,4,38,9000,1,1,1,1,1,1,9000
8
+ 1,1000,1,60.0,1000,120.0,8.0,3,56,1000,1,0,0,0,5,0,500
9
+ 1,12000,1,30.0,10000,560.0,2.0,3,38,9000,1,1,1,0,4,0,10000
10
+ 1,9000,1,,9000,1200.0,8.0,3,40,7000,1,1,0,1,4,0,6000
11
+ 1,6000,0,60.0,9500,900.0,7.0,2,28,9000,1,1,1,1,3,0,6000
12
+ 1,1000,1,60.0,4500,250.0,5.0,3,30,4500,0,1,1,1,1,0,800
13
+ 0,9000,1,36.0,42000,2000.0,4.0,1,54,9000,0,1,1,1,3,1,8500
14
+ 0,5000,1,60.0,2000,1500.0,10.0,1,35,2000,1,0,0,0,4,0,4000
15
+ 0,2000,0,60.0,8000,600.0,3.5,1,40,8000,0,0,1,0,3,0,2000
16
+ 0,8000,1,60.0,2000,100.0,1.0,3,40,5000,1,1,1,1,3,0,5000
17
+ 1,8000,1,15.0,3700,400.0,6.0,1,42,7000,0,0,0,0,1,0,5000
18
+ 0,3000,0,15.0,1900,460.0,7.0,2,37,5000,0,0,0,1,4,0,3000
19
+ 1,2500,0,36.0,10000,700.0,5.0,1,34,5000,1,0,1,1,5,0,2500
20
+ 1,12000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,7000
21
+ 0,500,1,30.0,5000,270.0,4.0,1,48,1000,0,0,0,1,1,0,485
22
+ 0,7000,1,30.0,7000,400.0,5.0,2,45,5000,0,0,1,1,4,0,5500
23
+ 0,10000,1,30.0,4000,400.0,8.0,4,60,9000,1,0,1,1,4,1,7000
24
+ 0,1000,0,36.0,5000,200.0,3.0,2,45,2000,0,1,1,1,4,1,1000
25
+ 1,700,0,30.0,7000,760.0,2.0,1,37,3000,1,0,0,0,1,0,700
26
+ 0,750,0,5.0,4500,250.0,2.0,2,36,3500,0,1,0,0,3,0,750
27
+ 1,1500,0,36.0,4000,720.0,10.0,1,45,3000,0,0,1,0,1,0,1500
28
+ 0,1500,1,30.0,3500,560.0,10.0,1,44,4000,0,0,1,0,1,0,1000
29
+ 1,2000,1,60.0,3140,600.0,15.0,1,31,1500,1,0,1,1,1,0,1500
30
+ 0,40000,0,60.0,100000,15000.0,6.0,1,42,7000,0,1,1,1,3,1,40000
31
+ 1,3000,0,60.0,10000,800.0,7.0,1,47,1000,0,0,1,0,1,0,3000
32
+ 0,500,0,15.0,7000,680.0,4.0,1,23,1000,0,1,1,1,4,0,500
33
+ 1,3000,1,30.0,6000,900.0,1.0,3,46,2000,0,0,0,1,4,0,1000
34
+ 0,3000,0,30.0,5000,450.0,3.0,2,34,4500,0,0,1,1,5,0,3000
35
+ 1,7000,1,12.0,1000,100.0,3.0,3,50,3000,1,0,0,1,4,0,3000
36
+ 1,3000,0,30.0,3700,400.0,3.0,1,45,8000,1,1,1,0,1,0,3000
37
+ 1,3000,0,36.0,5000,500.0,4.0,1,32,7000,0,0,1,1,4,0,3000
38
+ 1,600,0,60.0,3000,400.0,15.0,1,45,3000,1,1,1,0,3,0,600
39
+ 1,12000,1,,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,7000
40
+ 1,5000,1,30.0,4000,1400.0,4.0,1,48,3000,0,0,0,0,1,0,2000
41
+ 1,7000,1,,900,190.0,1.0,2,43,4000,0,1,0,0,4,0,5000
42
+ 0,2000,1,30.0,2450,749.0,2.0,1,25,1500,1,0,0,0,1,0,1500
43
+ 0,1000,0,30.0,2000,400.0,5.0,3,31,2000,0,0,0,1,5,0,1000
44
+ 1,300,0,30.0,2000,350.0,4.0,1,45,1000,1,0,1,0,1,0,300
45
+ 1,7000,1,60.0,5000,650.0,3.0,3,47,6000,1,1,0,0,4,0,5000
46
+ 1,300,0,60.0,6000,500.0,20.0,1,45,6000,1,1,1,0,1,0,300
47
+ 1,9000,1,,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,7000
48
+ 0,1500,0,60.0,3000,400.0,2.0,1,27,3000,0,0,1,1,5,0,1500
49
+ 0,9000,1,36.0,9000,700.0,3.0,3,55,9000,1,0,1,1,3,0,8000
50
+ 1,1000,0,30.0,2800,540.0,10.0,1,36,15000,1,0,1,0,1,0,1000
51
+ 0,9000,1,120.0,9000,700.0,3.0,3,55,9000,1,0,1,1,3,0,8000
52
+ 1,800,0,36.0,5000,400.0,3.0,1,35,2000,0,0,0,1,4,0,800
53
+ 1,5000,0,30.0,1000,180.0,4.0,4,40,7000,0,0,1,1,3,1,5000
54
+ 1,9000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,7000
55
+ 1,9000,1,60.0,9000,600.0,4.0,4,49,9000,1,1,0,1,4,0,8000
56
+ 1,30000,0,60.0,10000,500.0,1.0,1,45,80000,0,0,1,1,5,0,30000
57
+ 1,500,0,24.0,1000,200.0,2.0,2,35,700,0,0,1,1,4,0,500
58
+ 1,8000,0,120.0,2800,300.0,11.0,2,49,9000,1,0,1,0,2,0,8000
59
+ 0,10000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,8000
60
+ 0,2500,1,60.0,1300,180.0,9.0,1,43,2000,1,0,1,0,1,0,1300
61
+ 1,1000,0,12.0,3000,100.0,25.0,1,59,3000,0,0,1,1,1,0,1000
62
+ 0,17000,1,36.0,4000,450.0,15.0,1,40,4000,0,0,1,0,1,0,10000
63
+ 1,9000,1,60.0,8000,250.0,2.0,2,39,6000,1,1,1,0,2,0,5000
64
+ 1,700,1,20.0,1200,180.0,2.0,1,26,9700,0,0,0,1,4,0,600
65
+ 0,1000,0,30.0,2600,490.0,8.0,3,43,3000,0,0,1,1,5,0,1000
66
+ 1,12000,1,30.0,10000,568.0,2.0,3,38,8000,1,1,0,0,4,0,6000
67
+ 1,1000,0,20.0,1600,230.0,3.0,1,45,2500,0,0,0,1,4,0,1000
68
+ 0,300,0,30.0,3700,360.0,7.0,3,43,2000,0,0,1,1,4,0,300
69
+ 0,1500,0,30.0,3000,350.0,2.0,3,37,4000,0,0,0,1,5,0,1500
70
+ 1,9000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,7000
71
+ 0,1000,0,30.0,3000,560.0,10.0,1,34,15000,0,0,1,0,1,0,1000
72
+ 1,9000,1,60.0,9000,1200.0,8.0,3,40,7000,1,1,0,1,4,0,6000
73
+ 0,9000,1,30.0,8000,800.0,2.0,4,33,8000,0,0,1,0,4,1,6000
74
+ 0,20000,1,60.0,20000,1000.0,1.0,3,40,9000,1,1,1,1,4,0,10000
75
+ 1,10000,1,60.0,8000,250.0,2.0,2,39,6000,1,1,0,0,2,0,7000
76
+ 1,3000,0,60.0,3210,760.0,7.0,1,27,1500,1,0,1,0,1,0,3000
77
+ 0,300,0,60.0,1900,250.0,7.0,1,40,2000,0,0,0,0,1,0,300
78
+ 0,3000,0,30.0,12000,1400.0,2.0,3,32,5000,0,1,1,1,3,1,3000
79
+ 0,2500,0,30.0,5000,550.0,3.0,1,39,5000,1,0,1,0,1,0,2500
80
+ 1,1500,0,24.0,3000,300.0,4.0,1,33,2000,0,0,0,0,1,0,1500
81
+ 1,7000,0,60.0,3000,500.0,3.0,3,31,8000,0,1,1,1,5,0,7000
82
+ 1,12000,1,60.0,1800,200.0,7.0,2,42,5000,0,1,1,1,2,0,7000
83
+ 0,12000,1,60.0,2000,0.0,0.0,3,39,7000,0,1,0,0,1,0,5000
84
+ 0,10000,0,30.0,25000,1400.0,6.0,3,50,12000,1,1,1,0,3,1,10000
85
+ 1,10000,1,30.0,9000,2000.0,4.0,3,34,8900,0,1,1,1,4,0,7000
86
+ 0,600,1,60.0,600,125.0,12.0,1,59,2000,1,0,0,0,1,0,500
87
+ 0,10000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,8000
88
+ 0,1500,1,60.0,2200,170.0,6.0,1,42,7000,0,0,0,0,1,0,1200
89
+ 1,600,1,60.0,5000,680.0,20.0,3,45,5000,0,1,0,1,1,0,300
90
+ 1,3500,0,60.0,5000,285.0,12.0,2,35,4000,1,0,1,0,3,0,3500
91
+ 0,20000,0,60.0,40000,2500.0,3.0,3,54,8000,1,1,0,0,3,1,20000
92
+ 1,3000,0,30.0,6000,200.0,2.5,1,37,3000,0,0,0,1,1,0,3000
93
+ 0,6000,1,60.0,12000,1250.0,8.0,1,29,4000,1,1,0,0,1,0,5000
94
+ 1,10000,1,60.0,8000,250.0,2.0,2,39,6000,1,1,0,0,2,0,7000
95
+ 0,9000,0,30.0,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,9000
96
+ 1,8000,0,36.0,2800,300.0,5.0,2,49,9000,1,0,1,0,2,0,8000
97
+ 0,9000,0,30.0,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,9000
98
+ 1,1200,0,30.0,1500,155.0,7.0,1,39,1000,0,0,1,0,1,0,1200
99
+ 0,300,0,60.0,4300,400.0,9.0,1,44,3000,0,0,0,0,1,0,300
100
+ 1,12000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,7000
101
+ 1,1000,0,30.0,1000,350.0,1.0,3,36,3000,0,0,0,1,4,0,1000
102
+ 0,7000,1,30.0,7000,400.0,5.0,2,45,5000,0,0,0,1,4,0,5500
103
+ 1,3000,0,36.0,5000,500.0,4.0,1,39,7000,0,0,0,1,5,0,3000
104
+ 0,5000,0,30.0,8500,500.0,5.0,2,43,7000,0,0,1,1,3,0,5000
105
+ 0,9000,0,30.0,10000,900.0,3.0,3,35,9000,0,0,0,1,4,1,9000
106
+ 0,7000,0,60.0,15000,459.0,5.0,1,49,13000,0,0,1,1,5,0,7000
107
+ 1,1000,0,30.0,7000,800.0,11.0,1,44,3000,1,0,1,0,1,0,1000
108
+ 0,12000,1,30.0,10700,320.0,4.0,2,38,10000,1,1,1,1,3,0,10000
109
+ 1,3000,0,30.0,9500,1000.0,6.0,1,40,800,0,0,1,0,1,0,3000
110
+ 0,300,0,30.0,3000,30.0,1.0,2,28,3000,0,0,1,0,1,0,300
111
+ 0,300,0,30.0,10000,1800.0,6.0,2,35,1800,0,1,0,0,1,0,300
112
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113
+ 0,3000,1,30.0,4000,500.0,4.0,1,32,3500,0,0,1,1,4,0,2000
114
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115
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116
+ 1,10000,1,60.0,9000,600.0,4.0,4,49,9000,1,1,0,1,4,0,7000
117
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+ 1,5000,0,36.0,2000,500.0,17.0,1,42,2000,0,0,1,0,1,0,5000
train/loanpred_train.csv ADDED
@@ -0,0 +1,492 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Gender,Loan_ID,Gender,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_Status
2
+ Male,LP001273,Male,Yes,0,Graduate,No,6000,2250.0,265.0,360.0,,Semiurban,N
3
+ Male,LP001316,Male,Yes,0,Graduate,No,2958,2900.0,131.0,360.0,1.0,Semiurban,Y
4
+ Male,LP001758,Male,Yes,2,Graduate,No,6250,1695.0,210.0,360.0,1.0,Semiurban,Y
5
+ Male,LP002537,Male,Yes,0,Graduate,No,2083,3150.0,128.0,360.0,1.0,Semiurban,Y
6
+ Male,LP002493,Male,No,0,Graduate,No,4166,0.0,98.0,360.0,0.0,Semiurban,N
7
+ Male,LP002191,Male,Yes,0,Graduate,No,19730,5266.0,570.0,360.0,1.0,Rural,N
8
+ Male,LP001264,Male,Yes,3+,Not Graduate,Yes,3333,2166.0,130.0,360.0,,Semiurban,Y
9
+ ,LP001050,,Yes,2,Not Graduate,No,3365,1917.0,112.0,360.0,0.0,Rural,N
10
+ Female,LP001639,Female,Yes,0,Graduate,No,3625,0.0,108.0,360.0,1.0,Semiurban,Y
11
+ Male,LP001935,Male,No,0,Graduate,No,9508,0.0,187.0,360.0,1.0,Rural,Y
12
+ Male,LP002706,Male,Yes,1,Not Graduate,No,5285,1430.0,161.0,360.0,0.0,Semiurban,Y
13
+ Male,LP002862,Male,Yes,2,Not Graduate,No,6125,1625.0,187.0,480.0,1.0,Semiurban,N
14
+ Male,LP002369,Male,Yes,0,Graduate,No,2920,16.12000084,87.0,360.0,1.0,Rural,Y
15
+ Male,LP001574,Male,Yes,0,Graduate,No,3707,3166.0,182.0,,1.0,Rural,Y
16
+ Male,LP002319,Male,Yes,0,Graduate,,6256,0.0,160.0,360.0,,Urban,Y
17
+ Male,LP002699,Male,Yes,2,Graduate,Yes,17500,0.0,400.0,360.0,1.0,Rural,Y
18
+ Male,LP001020,Male,Yes,1,Graduate,No,12841,10968.0,349.0,360.0,1.0,Semiurban,N
19
+ Male,LP002175,Male,Yes,0,Graduate,No,4750,2333.0,130.0,360.0,1.0,Urban,Y
20
+ Male,LP002555,Male,Yes,2,Graduate,Yes,4583,2083.0,160.0,360.0,1.0,Semiurban,Y
21
+ Female,LP002367,Female,No,1,Not Graduate,No,4606,0.0,81.0,360.0,1.0,Rural,N
22
+ Female,LP002949,Female,No,3+,Graduate,,416,41667.0,350.0,180.0,,Urban,N
23
+ Male,LP002234,Male,No,0,Graduate,Yes,7167,0.0,128.0,360.0,1.0,Urban,Y
24
+ Male,LP001275,Male,Yes,1,Graduate,No,3988,0.0,50.0,240.0,1.0,Urban,Y
25
+ Male,LP001875,Male,No,0,Graduate,No,4095,3447.0,151.0,360.0,1.0,Rural,Y
26
+ Male,LP001673,Male,No,0,Graduate,Yes,11000,0.0,83.0,360.0,1.0,Urban,N
27
+ Male,LP002945,Male,Yes,0,Graduate,Yes,9963,0.0,180.0,360.0,1.0,Rural,Y
28
+ Male,LP002732,Male,No,0,Not Graduate,,2550,2042.0,126.0,360.0,1.0,Rural,Y
29
+ Female,LP002502,Female,Yes,2,Not Graduate,,210,2917.0,98.0,360.0,1.0,Semiurban,Y
30
+ Female,LP002894,Female,Yes,0,Graduate,No,3166,0.0,36.0,360.0,1.0,Semiurban,Y
31
+ Male,LP001938,Male,Yes,2,Graduate,No,4400,0.0,127.0,360.0,0.0,Semiurban,N
32
+ Male,LP001255,Male,No,0,Graduate,No,3750,0.0,113.0,480.0,1.0,Urban,N
33
+ Male,LP001319,Male,Yes,2,Not Graduate,No,3273,1820.0,81.0,360.0,1.0,Urban,Y
34
+ Male,LP001978,Male,No,0,Graduate,No,4000,2500.0,140.0,360.0,1.0,Rural,Y
35
+ Male,LP001238,Male,Yes,3+,Not Graduate,Yes,7100,0.0,125.0,60.0,1.0,Urban,Y
36
+ Male,LP001032,Male,No,0,Graduate,No,4950,0.0,125.0,360.0,1.0,Urban,Y
37
+ Male,LP001711,Male,Yes,3+,Graduate,No,3430,1250.0,128.0,360.0,0.0,Semiurban,N
38
+ Female,LP001883,Female,No,0,Graduate,,3418,0.0,135.0,360.0,1.0,Rural,N
39
+ Male,LP001289,Male,No,0,Graduate,No,8566,0.0,210.0,360.0,1.0,Urban,Y
40
+ Male,LP002652,Male,No,0,Graduate,No,5815,3666.0,311.0,360.0,1.0,Rural,N
41
+ Male,LP001405,Male,Yes,1,Graduate,No,2214,1398.0,85.0,360.0,,Urban,Y
42
+ Male,LP002272,Male,Yes,2,Graduate,No,3276,484.0,135.0,360.0,,Semiurban,Y
43
+ Male,LP002347,Male,Yes,0,Graduate,No,3246,1417.0,138.0,360.0,1.0,Semiurban,Y
44
+ Male,LP001098,Male,Yes,0,Graduate,No,3500,1667.0,114.0,360.0,1.0,Semiurban,Y
45
+ Male,LP001002,Male,No,0,Graduate,No,5849,0.0,,360.0,1.0,Urban,Y
46
+ Male,LP002964,Male,Yes,2,Not Graduate,No,3987,1411.0,157.0,360.0,1.0,Rural,Y
47
+ Male,LP001610,Male,Yes,3+,Graduate,No,5516,11300.0,495.0,360.0,0.0,Semiurban,N
48
+ Male,LP002149,Male,Yes,2,Graduate,No,8333,3167.0,165.0,360.0,1.0,Rural,Y
49
+ Female,LP002287,Female,No,0,Graduate,No,1500,1800.0,103.0,360.0,0.0,Semiurban,N
50
+ Male,LP002602,Male,No,0,Graduate,No,6283,4416.0,209.0,360.0,0.0,Rural,N
51
+ Male,LP001864,Male,Yes,3+,Not Graduate,No,4931,0.0,128.0,360.0,,Semiurban,N
52
+ Male,LP001047,Male,Yes,0,Not Graduate,No,2600,1911.0,116.0,360.0,0.0,Semiurban,N
53
+ Male,LP002459,Male,Yes,0,Graduate,No,4301,0.0,118.0,360.0,1.0,Urban,Y
54
+ Female,LP001404,Female,Yes,0,Graduate,No,3167,2283.0,154.0,360.0,1.0,Semiurban,Y
55
+ Male,LP001310,Male,Yes,0,Graduate,No,5695,4167.0,175.0,360.0,1.0,Semiurban,Y
56
+ Male,LP002898,Male,Yes,1,Graduate,No,1880,0.0,61.0,360.0,,Rural,N
57
+ Male,LP002422,Male,No,1,Graduate,No,37719,0.0,152.0,360.0,1.0,Semiurban,Y
58
+ Male,LP001038,Male,Yes,0,Not Graduate,No,4887,0.0,133.0,360.0,1.0,Rural,N
59
+ Male,LP002226,Male,Yes,0,Graduate,,3333,2500.0,128.0,360.0,1.0,Semiurban,Y
60
+ Male,LP002434,Male,Yes,2,Not Graduate,No,4652,0.0,110.0,360.0,1.0,Rural,Y
61
+ Male,LP001508,Male,Yes,2,Graduate,No,11757,0.0,187.0,180.0,1.0,Urban,Y
62
+ Male,LP001936,Male,Yes,0,Graduate,No,3075,2416.0,139.0,360.0,1.0,Rural,Y
63
+ Female,LP002142,Female,Yes,0,Graduate,Yes,5500,0.0,105.0,360.0,0.0,Rural,N
64
+ Male,LP002788,Male,Yes,0,Not Graduate,No,2454,2333.0,181.0,360.0,0.0,Urban,N
65
+ Male,LP002950,Male,Yes,0,Not Graduate,,2894,2792.0,155.0,360.0,1.0,Rural,Y
66
+ Male,LP001868,Male,No,0,Graduate,No,2060,2209.0,134.0,360.0,1.0,Semiurban,Y
67
+ Male,LP002587,Male,Yes,0,Not Graduate,No,2600,1700.0,107.0,360.0,1.0,Rural,Y
68
+ Male,LP002716,Male,No,0,Not Graduate,No,6783,0.0,130.0,360.0,1.0,Semiurban,Y
69
+ Female,LP002335,Female,Yes,0,Not Graduate,No,2149,3237.0,178.0,360.0,0.0,Semiurban,N
70
+ Male,LP001578,Male,Yes,0,Graduate,No,2439,3333.0,129.0,360.0,1.0,Rural,Y
71
+ Female,LP001186,Female,Yes,1,Graduate,Yes,11500,0.0,286.0,360.0,0.0,Urban,N
72
+ Male,LP001825,Male,Yes,0,Graduate,No,1809,1868.0,90.0,360.0,1.0,Urban,Y
73
+ Male,LP001138,Male,Yes,1,Graduate,No,5649,0.0,44.0,360.0,1.0,Urban,Y
74
+ Male,LP001322,Male,No,0,Graduate,No,4133,0.0,122.0,360.0,1.0,Semiurban,Y
75
+ Male,LP001892,Male,No,0,Graduate,No,2833,1857.0,126.0,360.0,1.0,Rural,Y
76
+ Male,LP001379,Male,Yes,2,Graduate,No,3800,3600.0,216.0,360.0,0.0,Urban,N
77
+ Male,LP001910,Male,No,1,Not Graduate,Yes,4053,2426.0,158.0,360.0,0.0,Urban,N
78
+ Male,LP001665,Male,Yes,1,Graduate,No,3125,2583.0,170.0,360.0,1.0,Semiurban,N
79
+ Female,LP002990,Female,No,0,Graduate,Yes,4583,0.0,133.0,360.0,0.0,Semiurban,N
80
+ Female,LP002586,Female,Yes,1,Graduate,No,3326,913.0,105.0,84.0,1.0,Semiurban,Y
81
+ Male,LP002447,Male,Yes,2,Not Graduate,No,1958,1456.0,60.0,300.0,,Urban,Y
82
+ Male,LP001811,Male,Yes,0,Not Graduate,No,3406,4417.0,123.0,360.0,1.0,Semiurban,Y
83
+ Male,LP002265,Male,Yes,2,Not Graduate,No,1993,1625.0,113.0,180.0,1.0,Semiurban,Y
84
+ Female,LP002002,Female,No,0,Graduate,No,2917,0.0,84.0,360.0,1.0,Semiurban,Y
85
+ Male,LP002315,Male,Yes,1,Graduate,No,8300,0.0,152.0,300.0,0.0,Semiurban,N
86
+ Male,LP002855,Male,Yes,2,Graduate,No,16666,0.0,275.0,360.0,1.0,Urban,Y
87
+ Male,LP001872,Male,No,0,Graduate,Yes,5166,0.0,128.0,360.0,1.0,Semiurban,Y
88
+ Male,LP002547,Male,Yes,1,Graduate,No,18333,0.0,500.0,360.0,1.0,Urban,N
89
+ Female,LP001241,Female,No,0,Graduate,No,4300,0.0,136.0,360.0,0.0,Semiurban,N
90
+ Male,LP002772,Male,No,0,Graduate,No,2526,1783.0,145.0,360.0,1.0,Rural,Y
91
+ Male,LP002342,Male,Yes,2,Graduate,Yes,1600,20000.0,239.0,360.0,1.0,Urban,N
92
+ Female,LP001925,Female,No,0,Graduate,Yes,2600,1717.0,99.0,300.0,1.0,Semiurban,N
93
+ Male,LP002738,Male,No,2,Graduate,No,3617,0.0,107.0,360.0,1.0,Semiurban,Y
94
+ Female,LP002741,Female,Yes,1,Graduate,No,4608,2845.0,140.0,180.0,1.0,Semiurban,Y
95
+ Female,LP001955,Female,No,0,Graduate,No,5000,2541.0,151.0,480.0,1.0,Rural,N
96
+ Male,LP001520,Male,Yes,0,Graduate,No,4860,830.0,125.0,360.0,1.0,Semiurban,Y
97
+ Male,LP001439,Male,Yes,0,Not Graduate,No,4300,2014.0,194.0,360.0,1.0,Rural,Y
98
+ Male,LP002418,Male,No,3+,Not Graduate,No,4707,1993.0,148.0,360.0,1.0,Semiurban,Y
99
+ Male,LP002536,Male,Yes,3+,Not Graduate,No,3095,0.0,113.0,360.0,1.0,Rural,Y
100
+ Male,LP001640,Male,Yes,0,Graduate,Yes,39147,4750.0,120.0,360.0,1.0,Semiurban,Y
101
+ Male,LP001819,Male,Yes,1,Not Graduate,No,6608,0.0,137.0,180.0,1.0,Urban,Y
102
+ Male,LP001963,Male,Yes,1,Graduate,No,2014,2925.0,113.0,360.0,1.0,Urban,N
103
+ Male,LP002705,Male,Yes,0,Graduate,No,3775,0.0,110.0,360.0,1.0,Semiurban,Y
104
+ Male,LP001891,Male,Yes,0,Graduate,No,11146,0.0,136.0,360.0,1.0,Urban,Y
105
+ Male,LP001907,Male,Yes,0,Graduate,No,14583,0.0,436.0,360.0,1.0,Semiurban,Y
106
+ Male,LP001095,Male,No,0,Graduate,No,3167,0.0,74.0,360.0,1.0,Urban,N
107
+ Male,LP002928,Male,Yes,0,Graduate,No,3000,3416.0,56.0,180.0,1.0,Semiurban,Y
108
+ Male,LP002692,Male,Yes,3+,Graduate,Yes,5677,1424.0,100.0,360.0,1.0,Rural,Y
109
+ Male,LP002888,Male,No,0,Graduate,,3182,2917.0,161.0,360.0,1.0,Urban,Y
110
+ Male,LP002515,Male,Yes,1,Graduate,Yes,3450,2079.0,162.0,360.0,1.0,Semiurban,Y
111
+ Male,LP002960,Male,Yes,0,Not Graduate,No,2400,3800.0,,180.0,1.0,Urban,N
112
+ Male,LP001398,Male,No,0,Graduate,,5050,0.0,118.0,360.0,1.0,Semiurban,Y
113
+ Male,LP001688,Male,Yes,1,Not Graduate,No,3500,1083.0,135.0,360.0,1.0,Urban,Y
114
+ Male,LP001498,Male,No,0,Graduate,No,5417,0.0,168.0,360.0,1.0,Urban,Y
115
+ Male,LP002138,Male,Yes,0,Graduate,No,2625,6250.0,187.0,360.0,1.0,Rural,Y
116
+ Male,LP001014,Male,Yes,3+,Graduate,No,3036,2504.0,158.0,360.0,0.0,Semiurban,N
117
+ Male,LP002729,Male,No,1,Graduate,No,11250,0.0,196.0,360.0,,Semiurban,N
118
+ Male,LP001041,Male,Yes,0,Graduate,,2600,3500.0,115.0,,1.0,Urban,Y
119
+ Male,LP001586,Male,Yes,3+,Not Graduate,No,3522,0.0,81.0,180.0,1.0,Rural,N
120
+ ,LP002501,,Yes,0,Graduate,No,16692,0.0,110.0,360.0,1.0,Semiurban,Y
121
+ Male,LP001195,Male,Yes,0,Graduate,No,2132,1591.0,96.0,360.0,1.0,Semiurban,Y
122
+ Female,LP002043,Female,No,1,Graduate,No,3541,0.0,112.0,360.0,,Semiurban,Y
123
+ Male,LP002130,Male,Yes,,Not Graduate,No,3523,3230.0,152.0,360.0,0.0,Rural,N
124
+ Male,LP002961,Male,Yes,1,Graduate,No,3400,2500.0,173.0,360.0,1.0,Semiurban,Y
125
+ Male,LP002100,Male,No,,Graduate,No,2833,0.0,71.0,360.0,1.0,Urban,Y
126
+ Male,LP002051,Male,Yes,0,Graduate,No,2400,2167.0,115.0,360.0,1.0,Semiurban,Y
127
+ Female,LP001151,Female,No,0,Graduate,No,4000,2275.0,144.0,360.0,1.0,Semiurban,Y
128
+ Male,LP001896,Male,Yes,2,Graduate,No,3900,0.0,90.0,360.0,1.0,Semiurban,Y
129
+ Male,LP001066,Male,Yes,0,Graduate,Yes,9560,0.0,191.0,360.0,1.0,Semiurban,Y
130
+ Male,LP002244,Male,Yes,0,Graduate,No,2333,2417.0,136.0,360.0,1.0,Urban,Y
131
+ Male,LP002958,Male,No,0,Graduate,No,3676,4301.0,172.0,360.0,1.0,Rural,Y
132
+ Male,LP001736,Male,Yes,0,Graduate,No,2221,0.0,60.0,360.0,0.0,Urban,N
133
+ Male,LP002387,Male,Yes,0,Graduate,No,2425,2340.0,143.0,360.0,1.0,Semiurban,Y
134
+ Male,LP001990,Male,No,0,Not Graduate,No,2000,0.0,,360.0,1.0,Urban,N
135
+ Male,LP001813,Male,No,0,Graduate,Yes,6050,4333.0,120.0,180.0,1.0,Urban,N
136
+ Female,LP002194,Female,No,0,Graduate,Yes,15759,0.0,55.0,360.0,1.0,Semiurban,Y
137
+ Male,LP001535,Male,No,0,Graduate,No,3254,0.0,50.0,360.0,1.0,Urban,Y
138
+ ,LP001448,,Yes,3+,Graduate,No,23803,0.0,370.0,360.0,1.0,Rural,Y
139
+ Female,LP002143,Female,Yes,0,Graduate,No,2423,505.0,130.0,360.0,1.0,Semiurban,Y
140
+ Female,LP001392,Female,No,1,Graduate,Yes,7451,0.0,,360.0,1.0,Semiurban,Y
141
+ Male,LP001594,Male,Yes,0,Graduate,No,5708,5625.0,187.0,360.0,1.0,Semiurban,Y
142
+ Male,LP001197,Male,Yes,0,Graduate,No,3366,2200.0,135.0,360.0,1.0,Rural,N
143
+ Male,LP002098,Male,No,0,Graduate,No,2935,0.0,98.0,360.0,1.0,Semiurban,Y
144
+ Male,LP001744,Male,No,0,Graduate,No,2971,2791.0,144.0,360.0,1.0,Semiurban,Y
145
+ Female,LP001036,Female,No,0,Graduate,No,3510,0.0,76.0,360.0,0.0,Urban,N
146
+ Female,LP002161,Female,No,1,Graduate,No,4723,0.0,81.0,360.0,1.0,Semiurban,N
147
+ Female,LP001846,Female,No,3+,Graduate,No,3083,0.0,255.0,360.0,1.0,Rural,Y
148
+ Male,LP002361,Male,Yes,0,Graduate,No,1820,1719.0,100.0,360.0,1.0,Urban,Y
149
+ Female,LP002917,Female,No,0,Not Graduate,No,2165,0.0,70.0,360.0,1.0,Semiurban,Y
150
+ Male,LP001653,Male,No,0,Not Graduate,No,4885,0.0,48.0,360.0,1.0,Rural,Y
151
+ Female,LP002086,Female,Yes,0,Graduate,No,4333,2451.0,110.0,360.0,1.0,Urban,N
152
+ Male,LP002740,Male,Yes,3+,Graduate,No,6417,0.0,157.0,180.0,1.0,Rural,Y
153
+ Male,LP002229,Male,No,0,Graduate,No,5941,4232.0,296.0,360.0,1.0,Semiurban,Y
154
+ Male,LP001325,Male,No,0,Not Graduate,No,3620,0.0,25.0,120.0,1.0,Semiurban,Y
155
+ Male,LP001633,Male,Yes,1,Graduate,No,6400,7250.0,180.0,360.0,0.0,Urban,N
156
+ Female,LP002116,Female,No,0,Graduate,No,2378,0.0,46.0,360.0,1.0,Rural,N
157
+ Female,LP002113,Female,No,3+,Not Graduate,No,1830,0.0,,360.0,0.0,Urban,N
158
+ Male,LP002053,Male,Yes,3+,Graduate,No,4342,189.0,124.0,360.0,1.0,Semiurban,Y
159
+ Male,LP001011,Male,Yes,2,Graduate,Yes,5417,4196.0,267.0,360.0,1.0,Urban,Y
160
+ Female,LP001137,Female,No,0,Graduate,No,3410,0.0,88.0,,1.0,Urban,Y
161
+ Female,LP001974,Female,No,0,Graduate,No,5000,0.0,132.0,360.0,1.0,Rural,Y
162
+ Male,LP002784,Male,Yes,1,Not Graduate,No,2492,2375.0,,360.0,1.0,Rural,Y
163
+ Male,LP002690,Male,No,0,Graduate,No,2500,0.0,55.0,360.0,1.0,Semiurban,Y
164
+ Male,LP001034,Male,No,1,Not Graduate,No,3596,0.0,100.0,240.0,,Urban,Y
165
+ Female,LP001146,Female,Yes,0,Graduate,No,2645,3440.0,120.0,360.0,0.0,Urban,N
166
+ Male,LP002936,Male,Yes,0,Graduate,No,3859,3300.0,142.0,180.0,1.0,Rural,Y
167
+ Male,LP002618,Male,Yes,1,Not Graduate,No,4050,5302.0,138.0,360.0,,Rural,N
168
+ Male,LP001006,Male,Yes,0,Not Graduate,No,2583,2358.0,120.0,360.0,1.0,Urban,Y
169
+ Male,LP002110,Male,Yes,1,Graduate,,5250,688.0,160.0,360.0,1.0,Rural,Y
170
+ Male,LP002449,Male,Yes,0,Graduate,No,2483,2466.0,90.0,180.0,0.0,Rural,Y
171
+ Female,LP002209,Female,No,0,Graduate,,2764,1459.0,110.0,360.0,1.0,Urban,Y
172
+ Male,LP002648,Male,Yes,0,Graduate,No,2130,6666.0,70.0,180.0,1.0,Semiurban,N
173
+ Male,LP002004,Male,No,0,Not Graduate,No,2927,2405.0,111.0,360.0,1.0,Semiurban,Y
174
+ Male,LP001751,Male,Yes,0,Graduate,No,3250,0.0,170.0,360.0,1.0,Rural,N
175
+ Male,LP001068,Male,Yes,0,Graduate,No,2799,2253.0,122.0,360.0,1.0,Semiurban,Y
176
+ Male,LP002403,Male,No,0,Graduate,Yes,10416,0.0,187.0,360.0,0.0,Urban,N
177
+ Female,LP001871,Female,No,0,Graduate,No,7200,0.0,120.0,360.0,1.0,Rural,Y
178
+ Female,LP001155,Female,Yes,0,Not Graduate,No,1928,1644.0,100.0,360.0,1.0,Semiurban,Y
179
+ Male,LP001761,Male,No,0,Graduate,Yes,6400,0.0,200.0,360.0,1.0,Rural,Y
180
+ Female,LP001112,Female,Yes,0,Graduate,No,3667,1459.0,144.0,360.0,1.0,Semiurban,Y
181
+ Male,LP001543,Male,Yes,1,Graduate,No,9538,0.0,187.0,360.0,1.0,Urban,Y
182
+ Female,LP001788,Female,No,0,Graduate,Yes,3463,0.0,122.0,360.0,,Urban,Y
183
+ ,LP002925,,No,0,Graduate,No,4750,0.0,94.0,360.0,1.0,Semiurban,Y
184
+ Male,LP001606,Male,Yes,0,Graduate,No,3497,1964.0,116.0,360.0,1.0,Rural,Y
185
+ Male,LP002659,Male,Yes,3+,Graduate,No,3466,3428.0,150.0,360.0,1.0,Rural,Y
186
+ Male,LP002624,Male,Yes,0,Graduate,No,20833,6667.0,480.0,360.0,,Urban,Y
187
+ Male,LP001664,Male,No,0,Graduate,No,4191,0.0,120.0,360.0,1.0,Rural,Y
188
+ Male,LP002682,Male,Yes,,Not Graduate,No,3074,1800.0,123.0,360.0,0.0,Semiurban,N
189
+ Male,LP002106,Male,Yes,,Graduate,Yes,5503,4490.0,70.0,,1.0,Semiurban,Y
190
+ ,LP002933,,No,3+,Graduate,Yes,9357,0.0,292.0,360.0,1.0,Semiurban,Y
191
+ Male,LP002693,Male,Yes,2,Graduate,Yes,7948,7166.0,480.0,360.0,1.0,Rural,Y
192
+ Male,LP001233,Male,Yes,1,Graduate,No,10750,0.0,312.0,360.0,1.0,Urban,Y
193
+ Female,LP002087,Female,No,0,Graduate,No,2500,0.0,67.0,360.0,1.0,Urban,Y
194
+ Male,LP001579,Male,No,0,Graduate,No,2237,0.0,63.0,480.0,0.0,Semiurban,N
195
+ ,LP002103,,Yes,1,Graduate,Yes,9833,1833.0,182.0,180.0,1.0,Urban,Y
196
+ Male,LP001565,Male,Yes,1,Graduate,No,3089,1280.0,121.0,360.0,0.0,Semiurban,N
197
+ Male,LP001998,Male,Yes,2,Not Graduate,No,7667,0.0,185.0,360.0,,Rural,Y
198
+ Male,LP001658,Male,No,0,Graduate,No,3858,0.0,76.0,360.0,1.0,Semiurban,Y
199
+ Male,LP001531,Male,No,0,Graduate,No,9166,0.0,244.0,360.0,1.0,Urban,N
200
+ Male,LP002151,Male,Yes,1,Graduate,No,3875,0.0,67.0,360.0,1.0,Urban,N
201
+ Male,LP002424,Male,Yes,0,Graduate,No,7333,8333.0,175.0,300.0,,Rural,Y
202
+ Female,LP002606,Female,No,0,Graduate,No,3159,0.0,100.0,360.0,1.0,Semiurban,Y
203
+ Male,LP002720,Male,Yes,3+,Graduate,No,4281,0.0,100.0,360.0,1.0,Urban,Y
204
+ Male,LP001356,Male,Yes,0,Graduate,No,4652,3583.0,,360.0,1.0,Semiurban,Y
205
+ Female,LP002301,Female,No,0,Graduate,Yes,7441,0.0,194.0,360.0,1.0,Rural,N
206
+ Male,LP001253,Male,Yes,3+,Graduate,Yes,5266,1774.0,187.0,360.0,1.0,Semiurban,Y
207
+ Male,LP002398,Male,No,0,Graduate,No,1926,1851.0,50.0,360.0,1.0,Semiurban,Y
208
+ Male,LP002931,Male,Yes,2,Graduate,Yes,6000,0.0,205.0,240.0,1.0,Semiurban,N
209
+ Female,LP001422,Female,No,0,Graduate,No,10408,0.0,259.0,360.0,1.0,Urban,Y
210
+ Male,LP002288,Male,Yes,2,Not Graduate,No,2889,0.0,45.0,180.0,0.0,Urban,N
211
+ Male,LP002362,Male,Yes,1,Graduate,No,7250,1667.0,110.0,,0.0,Urban,N
212
+ Male,LP002588,Male,Yes,0,Graduate,No,4625,2857.0,111.0,12.0,,Urban,Y
213
+ Male,LP001698,Male,No,0,Not Graduate,No,3975,2531.0,55.0,360.0,1.0,Rural,Y
214
+ Male,LP002128,Male,Yes,2,Graduate,,2583,2330.0,125.0,360.0,1.0,Rural,Y
215
+ Male,LP002180,Male,No,0,Graduate,Yes,6822,0.0,141.0,360.0,1.0,Rural,Y
216
+ Male,LP002141,Male,Yes,3+,Graduate,No,2666,2083.0,95.0,360.0,1.0,Rural,Y
217
+ Male,LP002697,Male,No,0,Graduate,No,4680,2087.0,,360.0,1.0,Semiurban,N
218
+ Male,LP001018,Male,Yes,2,Graduate,No,4006,1526.0,168.0,360.0,1.0,Urban,Y
219
+ Male,LP002255,Male,No,3+,Graduate,No,9167,0.0,185.0,360.0,1.0,Rural,Y
220
+ Male,LP001109,Male,Yes,0,Graduate,No,1828,1330.0,100.0,,0.0,Urban,N
221
+ Male,LP001493,Male,Yes,2,Not Graduate,No,4200,1430.0,129.0,360.0,1.0,Rural,N
222
+ Male,LP001843,Male,Yes,1,Not Graduate,No,2661,7101.0,279.0,180.0,1.0,Semiurban,Y
223
+ Male,LP001977,Male,Yes,1,Graduate,No,1625,1803.0,96.0,360.0,1.0,Urban,Y
224
+ Female,LP002300,Female,No,0,Not Graduate,No,1963,0.0,53.0,360.0,1.0,Semiurban,Y
225
+ Male,LP001199,Male,Yes,2,Not Graduate,No,3357,2859.0,144.0,360.0,1.0,Urban,Y
226
+ Female,LP001387,Female,Yes,0,Graduate,,2929,2333.0,139.0,360.0,1.0,Semiurban,Y
227
+ Male,LP002181,Male,No,0,Not Graduate,No,6216,0.0,133.0,360.0,1.0,Rural,N
228
+ Male,LP002211,Male,Yes,0,Graduate,No,4817,923.0,120.0,180.0,1.0,Urban,Y
229
+ Male,LP002821,Male,No,0,Not Graduate,Yes,5800,0.0,132.0,360.0,1.0,Semiurban,Y
230
+ Female,LP001870,Female,No,1,Graduate,No,3481,0.0,155.0,36.0,1.0,Semiurban,N
231
+ Male,LP002916,Male,Yes,0,Graduate,No,2297,1522.0,104.0,360.0,1.0,Urban,Y
232
+ Female,LP001954,Female,Yes,1,Graduate,No,4666,0.0,135.0,360.0,1.0,Urban,Y
233
+ Male,LP001528,Male,No,0,Graduate,No,6277,0.0,118.0,360.0,0.0,Rural,N
234
+ Male,LP001877,Male,Yes,2,Graduate,No,4708,1387.0,150.0,360.0,1.0,Semiurban,Y
235
+ Male,LP002717,Male,Yes,0,Graduate,No,1025,5500.0,216.0,360.0,,Rural,Y
236
+ Female,LP002753,Female,No,1,Graduate,,3652,0.0,95.0,360.0,1.0,Semiurban,Y
237
+ Male,LP001114,Male,No,0,Graduate,No,4166,7210.0,184.0,360.0,1.0,Urban,Y
238
+ Male,LP002435,Male,Yes,0,Graduate,,3539,1376.0,55.0,360.0,1.0,Rural,N
239
+ Female,LP001994,Female,No,0,Graduate,No,2400,1863.0,104.0,360.0,0.0,Urban,N
240
+ Female,LP001671,Female,Yes,0,Graduate,No,3416,2816.0,113.0,360.0,,Semiurban,Y
241
+ Female,LP002534,Female,No,0,Not Graduate,No,4350,0.0,154.0,360.0,1.0,Rural,Y
242
+ Male,LP002188,Male,No,0,Graduate,No,5124,0.0,124.0,,0.0,Rural,N
243
+ Female,LP001516,Female,Yes,2,Graduate,No,14866,0.0,70.0,360.0,1.0,Urban,Y
244
+ Male,LP002545,Male,No,2,Graduate,No,3547,0.0,80.0,360.0,0.0,Rural,N
245
+ Female,LP002757,Female,Yes,0,Not Graduate,No,3017,663.0,102.0,360.0,,Semiurban,Y
246
+ Male,LP001518,Male,Yes,1,Graduate,No,1538,1425.0,30.0,360.0,1.0,Urban,Y
247
+ Male,LP002390,Male,No,0,Graduate,No,3750,0.0,100.0,360.0,1.0,Urban,Y
248
+ Male,LP002137,Male,Yes,0,Graduate,No,6333,4583.0,259.0,360.0,,Semiurban,Y
249
+ Male,LP002067,Male,Yes,1,Graduate,Yes,8666,4983.0,376.0,360.0,0.0,Rural,N
250
+ Female,LP002305,Female,No,0,Graduate,No,4547,0.0,115.0,360.0,1.0,Semiurban,Y
251
+ Male,LP001432,Male,Yes,2,Graduate,No,2957,0.0,81.0,360.0,1.0,Semiurban,Y
252
+ Female,LP002670,Female,Yes,2,Graduate,No,2031,1632.0,113.0,480.0,1.0,Semiurban,Y
253
+ Female,LP001327,Female,Yes,0,Graduate,No,2484,2302.0,137.0,360.0,1.0,Semiurban,Y
254
+ Male,LP001507,Male,Yes,0,Graduate,No,2698,2034.0,122.0,360.0,1.0,Semiurban,Y
255
+ Male,LP001792,Male,Yes,1,Graduate,No,3315,0.0,96.0,360.0,1.0,Semiurban,Y
256
+ Male,LP002789,Male,Yes,0,Graduate,No,3593,4266.0,132.0,180.0,0.0,Rural,N
257
+ Male,LP001333,Male,Yes,0,Graduate,No,1977,997.0,50.0,360.0,1.0,Semiurban,Y
258
+ Male,LP002197,Male,Yes,2,Graduate,No,5185,0.0,155.0,360.0,1.0,Semiurban,Y
259
+ Male,LP002065,Male,Yes,3+,Graduate,No,15000,0.0,300.0,360.0,1.0,Rural,Y
260
+ Female,LP001908,Female,Yes,0,Not Graduate,No,4100,0.0,124.0,360.0,,Rural,Y
261
+ Female,LP001945,Female,No,,Graduate,No,5417,0.0,143.0,480.0,0.0,Urban,N
262
+ Female,LP002582,Female,No,0,Not Graduate,Yes,17263,0.0,225.0,360.0,1.0,Semiurban,Y
263
+ Female,LP001431,Female,No,0,Graduate,No,2137,8980.0,137.0,360.0,0.0,Semiurban,Y
264
+ Male,LP001637,Male,Yes,1,Graduate,No,33846,0.0,260.0,360.0,1.0,Semiurban,N
265
+ Male,LP001682,Male,Yes,3+,Not Graduate,No,3992,0.0,,180.0,1.0,Urban,N
266
+ Female,LP002055,Female,No,0,Graduate,No,3166,2985.0,132.0,360.0,,Rural,Y
267
+ Male,LP001814,Male,Yes,2,Graduate,No,9703,0.0,112.0,360.0,1.0,Urban,Y
268
+ Male,LP002386,Male,No,0,Graduate,,12876,0.0,405.0,360.0,1.0,Semiurban,Y
269
+ Male,LP002348,Male,Yes,0,Graduate,No,5829,0.0,138.0,360.0,1.0,Rural,Y
270
+ Male,LP002585,Male,Yes,0,Graduate,No,3597,2157.0,119.0,360.0,0.0,Rural,N
271
+ Male,LP002364,Male,Yes,0,Graduate,No,14880,0.0,96.0,360.0,1.0,Semiurban,Y
272
+ Female,LP002743,Female,No,0,Graduate,No,2138,0.0,99.0,360.0,0.0,Semiurban,N
273
+ Male,LP002297,Male,No,0,Graduate,No,2500,20000.0,103.0,360.0,1.0,Semiurban,Y
274
+ Female,LP001443,Female,No,0,Graduate,No,3692,0.0,93.0,360.0,,Rural,Y
275
+ Male,LP002768,Male,No,0,Not Graduate,No,3358,0.0,80.0,36.0,1.0,Semiurban,N
276
+ Female,LP002813,Female,Yes,1,Graduate,Yes,19484,0.0,600.0,360.0,1.0,Semiurban,Y
277
+ Male,LP001749,Male,Yes,0,Graduate,No,7578,1010.0,175.0,,1.0,Semiurban,Y
278
+ Male,LP002119,Male,Yes,1,Not Graduate,No,4554,1229.0,158.0,360.0,1.0,Urban,Y
279
+ Male,LP001179,Male,Yes,2,Graduate,No,4616,0.0,134.0,360.0,1.0,Urban,N
280
+ Female,LP001734,Female,Yes,2,Graduate,No,4283,2383.0,127.0,360.0,,Semiurban,Y
281
+ Male,LP001465,Male,Yes,0,Graduate,No,6080,2569.0,182.0,360.0,,Rural,N
282
+ Male,LP002792,Male,Yes,1,Graduate,No,5468,1032.0,26.0,360.0,1.0,Semiurban,Y
283
+ Female,LP002314,Female,No,0,Not Graduate,No,2213,0.0,66.0,360.0,1.0,Rural,Y
284
+ Female,LP002489,Female,No,1,Not Graduate,,5191,0.0,132.0,360.0,1.0,Semiurban,Y
285
+ Male,LP002795,Male,Yes,3+,Graduate,Yes,10139,0.0,260.0,360.0,1.0,Semiurban,Y
286
+ Male,LP002317,Male,Yes,3+,Graduate,No,81000,0.0,360.0,360.0,0.0,Rural,N
287
+ Female,LP002603,Female,No,0,Graduate,No,645,3683.0,113.0,480.0,1.0,Rural,Y
288
+ Female,LP002341,Female,No,1,Graduate,No,2600,0.0,160.0,360.0,1.0,Urban,N
289
+ Male,LP002239,Male,No,0,Not Graduate,No,2346,1600.0,132.0,360.0,1.0,Semiurban,Y
290
+ Male,LP002938,Male,Yes,0,Graduate,Yes,16120,0.0,260.0,360.0,1.0,Urban,Y
291
+ Male,LP001947,Male,Yes,0,Graduate,No,2383,3334.0,172.0,360.0,1.0,Semiurban,Y
292
+ Male,LP001882,Male,Yes,3+,Graduate,No,4333,1811.0,160.0,360.0,0.0,Urban,Y
293
+ ,LP002530,,Yes,2,Graduate,No,2873,1872.0,132.0,360.0,0.0,Semiurban,N
294
+ Male,LP002370,Male,No,0,Not Graduate,No,2717,0.0,60.0,180.0,1.0,Urban,Y
295
+ Male,LP001391,Male,Yes,0,Not Graduate,No,3572,4114.0,152.0,,0.0,Rural,N
296
+ Male,LP001630,Male,No,0,Not Graduate,No,2333,1451.0,102.0,480.0,0.0,Urban,N
297
+ Male,LP002984,Male,Yes,2,Graduate,No,7583,0.0,187.0,360.0,1.0,Urban,Y
298
+ Male,LP002785,Male,Yes,1,Graduate,No,3333,3250.0,158.0,360.0,1.0,Urban,Y
299
+ Male,LP002494,Male,No,0,Graduate,No,6000,0.0,140.0,360.0,1.0,Rural,Y
300
+ Male,LP002205,Male,No,1,Graduate,No,3062,1987.0,111.0,180.0,0.0,Urban,N
301
+ ,LP002024,,Yes,0,Graduate,No,2473,1843.0,159.0,360.0,1.0,Rural,N
302
+ Male,LP001529,Male,Yes,0,Graduate,Yes,2577,3750.0,152.0,360.0,1.0,Rural,Y
303
+ ,LP002625,,No,0,Graduate,No,3583,0.0,96.0,360.0,1.0,Urban,N
304
+ Female,LP001776,Female,No,0,Graduate,No,8333,0.0,280.0,360.0,1.0,Semiurban,Y
305
+ Female,LP001993,Female,No,0,Graduate,No,3762,1666.0,135.0,360.0,1.0,Rural,Y
306
+ Male,LP002409,Male,Yes,0,Graduate,No,7901,1833.0,180.0,360.0,1.0,Rural,Y
307
+ Male,LP001572,Male,Yes,0,Graduate,No,9323,0.0,75.0,180.0,1.0,Urban,Y
308
+ Male,LP002036,Male,Yes,0,Graduate,No,2058,2134.0,88.0,360.0,,Urban,Y
309
+ Female,LP001489,Female,Yes,0,Graduate,No,4583,0.0,84.0,360.0,1.0,Rural,N
310
+ Female,LP002318,Female,No,1,Not Graduate,Yes,3867,0.0,62.0,360.0,1.0,Semiurban,N
311
+ Female,LP001669,Female,No,0,Not Graduate,No,1907,2365.0,120.0,,1.0,Urban,Y
312
+ Male,LP002941,Male,Yes,2,Not Graduate,Yes,6383,1000.0,187.0,360.0,1.0,Rural,N
313
+ Male,LP001859,Male,Yes,0,Graduate,No,14683,2100.0,304.0,360.0,1.0,Rural,N
314
+ Male,LP001770,Male,No,0,Not Graduate,No,3189,2598.0,120.0,,1.0,Rural,Y
315
+ Male,LP001401,Male,Yes,1,Graduate,No,14583,0.0,185.0,180.0,1.0,Rural,Y
316
+ Male,LP001426,Male,Yes,,Graduate,No,5667,2667.0,180.0,360.0,1.0,Rural,Y
317
+ Male,LP002560,Male,No,0,Not Graduate,No,2699,2785.0,96.0,360.0,,Semiurban,Y
318
+ Male,LP002219,Male,Yes,3+,Graduate,No,8750,4996.0,130.0,360.0,1.0,Rural,Y
319
+ Male,LP002236,Male,Yes,2,Graduate,No,4566,0.0,100.0,360.0,1.0,Urban,N
320
+ Male,LP001750,Male,Yes,0,Graduate,No,6250,0.0,128.0,360.0,1.0,Semiurban,Y
321
+ Male,LP002893,Male,No,0,Graduate,No,1836,33837.0,90.0,360.0,1.0,Urban,N
322
+ Male,LP002519,Male,Yes,3+,Graduate,No,4691,0.0,100.0,360.0,1.0,Semiurban,Y
323
+ Male,LP002131,Male,Yes,2,Not Graduate,No,3083,2168.0,126.0,360.0,1.0,Urban,Y
324
+ Male,LP001449,Male,No,0,Graduate,No,3865,1640.0,,360.0,1.0,Rural,Y
325
+ Female,LP002959,Female,Yes,1,Graduate,No,12000,0.0,496.0,360.0,1.0,Semiurban,Y
326
+ Male,LP002429,Male,Yes,1,Graduate,Yes,3466,1210.0,130.0,360.0,1.0,Rural,Y
327
+ Male,LP001924,Male,No,0,Graduate,No,3158,3053.0,89.0,360.0,1.0,Rural,Y
328
+ Male,LP002833,Male,Yes,0,Not Graduate,No,4467,0.0,120.0,360.0,,Rural,Y
329
+ Male,LP001131,Male,Yes,0,Graduate,No,3941,2336.0,134.0,360.0,1.0,Semiurban,Y
330
+ Male,LP001370,Male,No,0,Not Graduate,,7333,0.0,120.0,360.0,1.0,Rural,N
331
+ Male,LP002683,Male,No,0,Graduate,No,4683,1915.0,185.0,360.0,1.0,Semiurban,N
332
+ Male,LP002541,Male,Yes,0,Graduate,No,10833,0.0,234.0,360.0,1.0,Semiurban,Y
333
+ Male,LP001482,Male,Yes,0,Graduate,Yes,3459,0.0,25.0,120.0,1.0,Semiurban,Y
334
+ Male,LP002408,Male,No,0,Graduate,No,3660,5064.0,187.0,360.0,1.0,Semiurban,Y
335
+ Male,LP002640,Male,Yes,1,Graduate,No,6065,2004.0,250.0,360.0,1.0,Semiurban,Y
336
+ Male,LP001136,Male,Yes,0,Not Graduate,Yes,4695,0.0,96.0,,1.0,Urban,Y
337
+ Male,LP001580,Male,Yes,2,Graduate,No,8000,0.0,200.0,360.0,1.0,Semiurban,Y
338
+ Male,LP001225,Male,Yes,0,Graduate,No,5726,4595.0,258.0,360.0,1.0,Semiurban,N
339
+ Female,LP001917,Female,No,0,Graduate,No,1811,1666.0,54.0,360.0,1.0,Urban,Y
340
+ Male,LP001279,Male,No,0,Graduate,No,2366,2531.0,136.0,360.0,1.0,Semiurban,Y
341
+ Male,LP001806,Male,No,0,Graduate,No,2965,5701.0,155.0,60.0,1.0,Urban,Y
342
+ Male,LP001641,Male,Yes,1,Graduate,Yes,2178,0.0,66.0,300.0,0.0,Rural,N
343
+ Male,LP002068,Male,No,0,Graduate,No,4917,0.0,130.0,360.0,0.0,Rural,Y
344
+ Male,LP001552,Male,Yes,0,Graduate,No,4583,5625.0,255.0,360.0,1.0,Semiurban,Y
345
+ Male,LP001028,Male,Yes,2,Graduate,No,3073,8106.0,200.0,360.0,1.0,Urban,Y
346
+ Male,LP001106,Male,Yes,0,Graduate,No,2275,2067.0,,360.0,1.0,Urban,Y
347
+ Male,LP001086,Male,No,0,Not Graduate,No,1442,0.0,35.0,360.0,1.0,Urban,N
348
+ Male,LP001581,Male,Yes,0,Not Graduate,,1820,1769.0,95.0,360.0,1.0,Rural,Y
349
+ Male,LP001504,Male,No,0,Graduate,Yes,6950,0.0,175.0,180.0,1.0,Semiurban,Y
350
+ Male,LP001786,Male,Yes,0,Graduate,,5746,0.0,255.0,360.0,,Urban,N
351
+ Male,LP002533,Male,Yes,2,Graduate,No,2947,1603.0,,360.0,1.0,Urban,N
352
+ Male,LP002643,Male,Yes,2,Graduate,No,3283,2035.0,148.0,360.0,1.0,Urban,Y
353
+ Male,LP001743,Male,Yes,2,Graduate,No,4009,1717.0,116.0,360.0,1.0,Semiurban,Y
354
+ Female,LP002794,Female,No,0,Graduate,No,2667,1625.0,84.0,360.0,,Urban,Y
355
+ Male,LP001326,Male,No,0,Graduate,,6782,0.0,,360.0,,Urban,N
356
+ Female,LP001157,Female,No,0,Graduate,No,3086,0.0,120.0,360.0,1.0,Semiurban,Y
357
+ Male,LP001798,Male,Yes,2,Graduate,No,5819,5000.0,120.0,360.0,1.0,Rural,Y
358
+ Male,LP002723,Male,No,2,Graduate,No,3588,0.0,110.0,360.0,0.0,Rural,N
359
+ Male,LP002140,Male,No,0,Graduate,No,8750,4167.0,308.0,360.0,1.0,Rural,N
360
+ Male,LP002714,Male,No,1,Not Graduate,No,2679,1302.0,94.0,360.0,1.0,Semiurban,Y
361
+ Male,LP001616,Male,Yes,1,Graduate,No,3750,0.0,116.0,360.0,1.0,Semiurban,Y
362
+ ,LP002478,,Yes,0,Graduate,Yes,2083,4083.0,160.0,360.0,,Semiurban,Y
363
+ Male,LP002739,Male,Yes,0,Not Graduate,No,2917,536.0,66.0,360.0,1.0,Rural,N
364
+ Male,LP001120,Male,No,0,Graduate,No,1800,1213.0,47.0,360.0,1.0,Urban,Y
365
+ Male,LP002837,Male,Yes,3+,Graduate,No,3400,2500.0,123.0,360.0,0.0,Rural,N
366
+ Female,LP002731,Female,No,0,Not Graduate,Yes,18165,0.0,125.0,360.0,1.0,Urban,Y
367
+ Female,LP001693,Female,No,0,Graduate,No,3244,0.0,80.0,360.0,1.0,Urban,Y
368
+ Male,LP002263,Male,Yes,0,Graduate,No,2583,2115.0,120.0,360.0,,Urban,Y
369
+ Male,LP001915,Male,Yes,2,Graduate,No,2301,985.7999878,78.0,180.0,1.0,Urban,Y
370
+ Male,LP002158,Male,Yes,0,Not Graduate,No,3000,1666.0,100.0,480.0,0.0,Urban,N
371
+ Male,LP002281,Male,Yes,0,Graduate,No,3033,1459.0,95.0,360.0,1.0,Urban,Y
372
+ Male,LP001844,Male,No,0,Graduate,Yes,16250,0.0,192.0,360.0,0.0,Urban,N
373
+ Male,LP001726,Male,Yes,0,Graduate,No,3727,1775.0,131.0,360.0,1.0,Semiurban,Y
374
+ Male,LP001008,Male,No,0,Graduate,No,6000,0.0,141.0,360.0,1.0,Urban,Y
375
+ Male,LP001849,Male,No,0,Not Graduate,No,6045,0.0,115.0,360.0,0.0,Rural,N
376
+ ,LP002872,,Yes,0,Graduate,No,3087,2210.0,136.0,360.0,0.0,Semiurban,N
377
+ Male,LP002767,Male,Yes,0,Graduate,No,2768,1950.0,155.0,360.0,1.0,Rural,Y
378
+ Female,LP002377,Female,No,1,Graduate,Yes,8624,0.0,150.0,360.0,1.0,Semiurban,Y
379
+ Male,LP001345,Male,Yes,2,Not Graduate,No,4288,3263.0,133.0,180.0,1.0,Urban,Y
380
+ Male,LP001754,Male,Yes,,Not Graduate,Yes,4735,0.0,138.0,360.0,1.0,Urban,N
381
+ Male,LP002443,Male,Yes,2,Graduate,No,3340,1710.0,150.0,360.0,0.0,Rural,N
382
+ Female,LP002804,Female,Yes,0,Graduate,No,4180,2306.0,182.0,360.0,1.0,Semiurban,Y
383
+ Male,LP002912,Male,Yes,1,Graduate,No,4283,3000.0,172.0,84.0,1.0,Rural,N
384
+ Male,LP001715,Male,Yes,3+,Not Graduate,Yes,5703,0.0,130.0,360.0,1.0,Rural,Y
385
+ Male,LP002160,Male,Yes,3+,Graduate,No,5167,3167.0,200.0,360.0,1.0,Semiurban,Y
386
+ ,LP001585,,Yes,3+,Graduate,No,51763,0.0,700.0,300.0,1.0,Urban,Y
387
+ Male,LP001334,Male,Yes,0,Not Graduate,No,4188,0.0,115.0,180.0,1.0,Semiurban,Y
388
+ Male,LP001940,Male,Yes,2,Graduate,No,3153,1560.0,134.0,360.0,1.0,Urban,Y
389
+ Male,LP001720,Male,Yes,3+,Not Graduate,No,3850,983.0,100.0,360.0,1.0,Semiurban,Y
390
+ Male,LP001206,Male,Yes,3+,Graduate,No,3029,0.0,99.0,360.0,1.0,Urban,Y
391
+ Male,LP002308,Male,Yes,0,Not Graduate,No,2167,2400.0,115.0,360.0,1.0,Urban,Y
392
+ Male,LP002615,Male,Yes,2,Graduate,No,4865,5624.0,208.0,360.0,1.0,Semiurban,Y
393
+ Male,LP001144,Male,Yes,0,Graduate,No,5821,0.0,144.0,360.0,1.0,Urban,Y
394
+ Male,LP001097,Male,No,1,Graduate,Yes,4692,0.0,106.0,360.0,1.0,Rural,N
395
+ Male,LP001674,Male,Yes,1,Not Graduate,No,2600,2500.0,90.0,360.0,1.0,Semiurban,Y
396
+ Male,LP001487,Male,No,0,Graduate,No,4895,0.0,102.0,360.0,1.0,Semiurban,Y
397
+ Male,LP001073,Male,Yes,2,Not Graduate,No,4226,1040.0,110.0,360.0,1.0,Urban,Y
398
+ Male,LP002734,Male,Yes,0,Graduate,No,6133,3906.0,324.0,360.0,1.0,Urban,Y
399
+ Male,LP001765,Male,Yes,1,Graduate,No,2491,2054.0,104.0,360.0,1.0,Semiurban,Y
400
+ Male,LP002556,Male,No,0,Graduate,No,2435,0.0,75.0,360.0,1.0,Urban,N
401
+ Male,LP002224,Male,No,0,Graduate,No,3069,0.0,71.0,480.0,1.0,Urban,N
402
+ Female,LP001931,Female,No,0,Graduate,No,4124,0.0,115.0,360.0,1.0,Semiurban,Y
403
+ Male,LP002345,Male,Yes,0,Graduate,No,1025,2773.0,112.0,360.0,1.0,Rural,Y
404
+ Male,LP002262,Male,Yes,3+,Graduate,No,9504,0.0,275.0,360.0,1.0,Rural,Y
405
+ Male,LP002600,Male,Yes,1,Graduate,Yes,2895,0.0,95.0,360.0,1.0,Semiurban,Y
406
+ Male,LP001492,Male,No,0,Graduate,No,14999,0.0,242.0,360.0,0.0,Semiurban,N
407
+ Male,LP001207,Male,Yes,0,Not Graduate,Yes,2609,3449.0,165.0,180.0,0.0,Rural,N
408
+ Male,LP002517,Male,Yes,1,Not Graduate,No,2653,1500.0,113.0,180.0,0.0,Rural,N
409
+ Male,LP001451,Male,Yes,1,Graduate,Yes,10513,3850.0,160.0,180.0,0.0,Urban,N
410
+ Male,LP002943,Male,No,,Graduate,No,2987,0.0,88.0,360.0,0.0,Semiurban,N
411
+ Male,LP002689,Male,Yes,2,Not Graduate,No,2192,1742.0,45.0,360.0,1.0,Semiurban,Y
412
+ Female,LP001222,Female,No,0,Graduate,No,4166,0.0,116.0,360.0,0.0,Semiurban,N
413
+ Male,LP001030,Male,Yes,2,Graduate,No,1299,1086.0,17.0,120.0,1.0,Urban,Y
414
+ Male,LP001541,Male,Yes,1,Graduate,No,6000,0.0,160.0,360.0,,Rural,Y
415
+ Male,LP001119,Male,No,0,Graduate,No,3600,0.0,80.0,360.0,1.0,Urban,N
416
+ Male,LP002571,Male,No,0,Not Graduate,No,3691,0.0,110.0,360.0,1.0,Rural,Y
417
+ Male,LP002225,Male,Yes,2,Graduate,No,5391,0.0,130.0,360.0,1.0,Urban,Y
418
+ Male,LP001643,Male,Yes,0,Graduate,No,2383,2138.0,58.0,360.0,,Rural,Y
419
+ Male,LP001722,Male,Yes,0,Graduate,No,150,1800.0,135.0,360.0,1.0,Rural,N
420
+ Female,LP001164,Female,No,0,Graduate,No,4230,0.0,112.0,360.0,1.0,Semiurban,N
421
+ Male,LP002112,Male,Yes,2,Graduate,Yes,2500,4600.0,176.0,360.0,1.0,Rural,Y
422
+ Male,LP001949,Male,Yes,3+,Graduate,,4416,1250.0,110.0,360.0,1.0,Urban,Y
423
+ Female,LP001836,Female,No,2,Graduate,No,3427,0.0,138.0,360.0,1.0,Urban,N
424
+ Male,LP002484,Male,Yes,3+,Graduate,No,7740,0.0,128.0,180.0,1.0,Urban,Y
425
+ Male,LP002455,Male,Yes,2,Graduate,No,3859,0.0,96.0,360.0,1.0,Semiurban,Y
426
+ Male,LP002983,Male,Yes,1,Graduate,No,8072,240.0,253.0,360.0,1.0,Urban,Y
427
+ Female,LP001884,Female,No,1,Graduate,No,2876,1560.0,90.0,360.0,1.0,Urban,Y
428
+ Male,LP001677,Male,No,2,Graduate,No,4923,0.0,166.0,360.0,0.0,Semiurban,Y
429
+ Male,LP001562,Male,Yes,0,Graduate,No,7933,0.0,275.0,360.0,1.0,Urban,N
430
+ Male,LP002296,Male,No,0,Not Graduate,No,2755,0.0,65.0,300.0,1.0,Rural,N
431
+ Male,LP002529,Male,Yes,2,Graduate,No,6700,1750.0,230.0,300.0,1.0,Semiurban,Y
432
+ Male,LP001367,Male,Yes,1,Graduate,No,3052,1030.0,100.0,360.0,1.0,Urban,Y
433
+ Male,LP002250,Male,Yes,0,Graduate,No,5488,0.0,125.0,360.0,1.0,Rural,Y
434
+ Male,LP001003,Male,Yes,1,Graduate,No,4583,1508.0,128.0,360.0,1.0,Rural,N
435
+ Male,LP002847,Male,Yes,,Graduate,No,5116,1451.0,165.0,360.0,0.0,Urban,N
436
+ Female,LP001265,Female,No,0,Graduate,No,3846,0.0,111.0,360.0,1.0,Semiurban,Y
437
+ Female,LP001692,Female,No,0,Not Graduate,No,4408,0.0,120.0,360.0,1.0,Semiurban,Y
438
+ Male,LP001100,Male,No,3+,Graduate,No,12500,3000.0,320.0,360.0,1.0,Rural,N
439
+ Male,LP002626,Male,Yes,0,Graduate,Yes,2479,3013.0,188.0,360.0,1.0,Urban,Y
440
+ Male,LP002368,Male,Yes,2,Graduate,No,5935,0.0,133.0,360.0,1.0,Semiurban,Y
441
+ Male,LP002453,Male,No,0,Graduate,Yes,7085,0.0,84.0,360.0,1.0,Semiurban,Y
442
+ Male,LP002187,Male,No,0,Graduate,No,2500,0.0,96.0,480.0,1.0,Semiurban,N
443
+ Male,LP001318,Male,Yes,2,Graduate,No,6250,5654.0,188.0,180.0,1.0,Semiurban,Y
444
+ Female,LP002114,Female,No,0,Graduate,No,4160,0.0,71.0,360.0,1.0,Semiurban,Y
445
+ Male,LP002832,Male,Yes,2,Graduate,No,8799,0.0,258.0,360.0,0.0,Urban,N
446
+ Male,LP002129,Male,Yes,0,Graduate,No,2499,2458.0,160.0,360.0,1.0,Semiurban,Y
447
+ Male,LP001800,Male,Yes,1,Not Graduate,No,2510,1983.0,140.0,180.0,1.0,Urban,N
448
+ Male,LP001029,Male,No,0,Graduate,No,1853,2840.0,114.0,360.0,1.0,Rural,N
449
+ Male,LP002031,Male,Yes,1,Not Graduate,No,3399,1640.0,111.0,180.0,1.0,Urban,Y
450
+ Male,LP002243,Male,Yes,0,Not Graduate,No,3010,3136.0,,360.0,0.0,Urban,N
451
+ Male,LP001894,Male,Yes,0,Graduate,No,2620,2223.0,150.0,360.0,1.0,Semiurban,Y
452
+ Female,LP001577,Female,Yes,0,Graduate,No,4583,0.0,112.0,360.0,1.0,Rural,N
453
+ Male,LP002974,Male,Yes,0,Graduate,No,3232,1950.0,108.0,360.0,1.0,Rural,Y
454
+ Male,LP002543,Male,Yes,2,Graduate,No,8333,0.0,246.0,360.0,1.0,Semiurban,Y
455
+ Male,LP002948,Male,Yes,2,Graduate,No,5780,0.0,192.0,360.0,1.0,Urban,Y
456
+ Male,LP002619,Male,Yes,0,Not Graduate,No,3814,1483.0,124.0,300.0,1.0,Semiurban,Y
457
+ Male,LP001807,Male,Yes,2,Graduate,Yes,6250,1300.0,108.0,360.0,1.0,Rural,Y
458
+ Male,LP002836,Male,No,0,Graduate,No,3333,0.0,70.0,360.0,1.0,Urban,Y
459
+ Male,LP002820,Male,Yes,0,Graduate,No,5923,2054.0,211.0,360.0,1.0,Rural,Y
460
+ Male,LP001647,Male,Yes,0,Graduate,No,9328,0.0,188.0,180.0,1.0,Rural,Y
461
+ Male,LP002527,Male,Yes,2,Graduate,Yes,16525,1014.0,150.0,360.0,1.0,Rural,Y
462
+ Male,LP002637,Male,No,0,Not Graduate,No,3598,1287.0,100.0,360.0,1.0,Rural,N
463
+ Male,LP001198,Male,Yes,1,Graduate,No,8080,2250.0,180.0,360.0,1.0,Urban,Y
464
+ Male,LP002524,Male,No,2,Graduate,No,5532,4648.0,162.0,360.0,1.0,Rural,Y
465
+ Male,LP002807,Male,Yes,2,Not Graduate,No,3675,242.0,108.0,360.0,1.0,Semiurban,Y
466
+ Male,LP001841,Male,No,0,Not Graduate,Yes,2583,2167.0,104.0,360.0,1.0,Rural,Y
467
+ Male,LP001046,Male,Yes,1,Graduate,No,5955,5625.0,315.0,360.0,1.0,Urban,Y
468
+ Male,LP002008,Male,Yes,2,Graduate,Yes,5746,0.0,144.0,84.0,,Rural,Y
469
+ Male,LP002473,Male,Yes,0,Graduate,No,8334,0.0,160.0,360.0,1.0,Semiurban,N
470
+ Male,LP001560,Male,Yes,0,Not Graduate,No,1863,1041.0,98.0,360.0,1.0,Semiurban,Y
471
+ Male,LP001903,Male,Yes,0,Graduate,No,3993,3274.0,207.0,360.0,1.0,Semiurban,Y
472
+ Male,LP001656,Male,No,0,Graduate,No,12000,0.0,164.0,360.0,1.0,Semiurban,N
473
+ Male,LP002237,Male,No,1,Graduate,,3667,0.0,113.0,180.0,1.0,Urban,Y
474
+ Male,LP002332,Male,Yes,0,Not Graduate,No,2253,2033.0,110.0,360.0,1.0,Rural,Y
475
+ Male,LP002562,Male,Yes,1,Not Graduate,No,5333,1131.0,186.0,360.0,,Urban,Y
476
+ Male,LP002126,Male,Yes,3+,Not Graduate,No,3173,0.0,74.0,360.0,1.0,Semiurban,Y
477
+ Male,LP001996,Male,No,0,Graduate,No,20233,0.0,480.0,360.0,1.0,Rural,N
478
+ Male,LP001469,Male,No,0,Graduate,Yes,20166,0.0,650.0,480.0,,Urban,Y
479
+ Male,LP001343,Male,Yes,0,Graduate,No,1759,3541.0,131.0,360.0,1.0,Semiurban,Y
480
+ Male,LP002201,Male,Yes,2,Graduate,Yes,9323,7873.0,380.0,300.0,1.0,Rural,Y
481
+ Male,LP001282,Male,Yes,0,Graduate,No,2500,2118.0,104.0,360.0,1.0,Semiurban,Y
482
+ Male,LP002472,Male,No,2,Graduate,No,4354,0.0,136.0,360.0,1.0,Rural,Y
483
+ Male,LP002097,Male,No,1,Graduate,No,4384,1793.0,117.0,360.0,1.0,Urban,Y
484
+ Male,LP001716,Male,Yes,0,Graduate,No,3173,3021.0,137.0,360.0,1.0,Urban,Y
485
+ Male,LP002500,Male,Yes,3+,Not Graduate,No,2947,1664.0,70.0,180.0,0.0,Urban,N
486
+ Female,LP001430,Female,No,0,Graduate,No,4166,0.0,44.0,360.0,1.0,Semiurban,Y
487
+ Male,LP001043,Male,Yes,0,Not Graduate,No,7660,0.0,104.0,360.0,0.0,Urban,N
488
+ Male,LP001245,Male,Yes,2,Not Graduate,Yes,1875,1875.0,97.0,360.0,1.0,Semiurban,Y
489
+ Male,LP001369,Male,Yes,2,Graduate,No,11417,1126.0,225.0,360.0,1.0,Urban,Y
490
+ Female,LP001888,Female,No,0,Graduate,No,3237,0.0,30.0,360.0,1.0,Urban,Y
491
+ Female,LP002393,Female,,,Graduate,No,10047,0.0,,240.0,1.0,Semiurban,Y
492
+ Male,LP001350,Male,Yes,,Graduate,No,13650,0.0,,360.0,1.0,Urban,Y
train/modifiedghana_train.csv ADDED
@@ -0,0 +1,1161 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ sex,amnt req,amnt grnt,ration,maturity,assets val,dec profit,xperience,educatn,age,collateral,locatn,guarantor,relatnshp,purpose,sector,savings,target
2
+ 0,2000,2000,0,36.0,4000,500.0,3.0,1,28,900,0,0,1,0,1,0,Yes
3
+ 1,1000,1000,0,30.0,3000,600.0,6.0,2,35,3000,0,0,0,1,1,0,Yes
4
+ 0,5000,3000,1,40.0,7000,1350.0,5.0,3,35,2000,0,0,1,1,4,0,No
5
+ 0,1000,1000,0,24.0,2500,590.0,6.0,1,25,20000,1,0,1,0,1,0,Yes
6
+ 1,2000,2000,0,60.0,2800,320.0,12.0,3,42,2000,0,0,0,1,5,0,Yes
7
+ 0,9000,9000,0,30.0,5000,320.0,9.0,4,38,9000,1,1,1,1,1,1,Yes
8
+ 1,1000,500,1,60.0,1000,120.0,8.0,3,56,1000,1,0,0,0,5,0,No
9
+ 1,12000,10000,1,30.0,10000,560.0,2.0,3,38,9000,1,1,1,0,4,0,No
10
+ 1,9000,6000,1,,9000,1200.0,8.0,3,40,7000,1,1,0,1,4,0,No
11
+ 1,6000,6000,0,60.0,9500,900.0,7.0,2,28,9000,1,1,1,1,3,0,Yes
12
+ 1,1000,800,1,60.0,4500,250.0,5.0,3,30,4500,0,1,1,1,1,0,No
13
+ 0,9000,8500,1,36.0,42000,2000.0,4.0,1,54,9000,0,1,1,1,3,1,No
14
+ 0,5000,4000,1,60.0,2000,1500.0,10.0,1,35,2000,1,0,0,0,4,0,No
15
+ 0,2000,2000,0,60.0,8000,600.0,3.5,1,40,8000,0,0,1,0,3,0,Yes
16
+ 0,8000,5000,1,60.0,2000,100.0,1.0,3,40,5000,1,1,1,1,3,0,No
17
+ 1,8000,5000,1,15.0,3700,400.0,6.0,1,42,7000,0,0,0,0,1,0,No
18
+ 0,3000,3000,0,15.0,1900,460.0,7.0,2,37,5000,0,0,0,1,4,0,Yes
19
+ 1,2500,2500,0,36.0,10000,700.0,5.0,1,34,5000,1,0,1,1,5,0,Yes
20
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
21
+ 0,500,485,1,30.0,5000,270.0,4.0,1,48,1000,0,0,0,1,1,0,No
22
+ 0,7000,5500,1,30.0,7000,400.0,5.0,2,45,5000,0,0,1,1,4,0,No
23
+ 0,10000,7000,1,30.0,4000,400.0,8.0,4,60,9000,1,0,1,1,4,1,No
24
+ 0,1000,1000,0,36.0,5000,200.0,3.0,2,45,2000,0,1,1,1,4,1,Yes
25
+ 1,700,700,0,30.0,7000,760.0,2.0,1,37,3000,1,0,0,0,1,0,Yes
26
+ 0,750,750,0,5.0,4500,250.0,2.0,2,36,3500,0,1,0,0,3,0,Yes
27
+ 1,1500,1500,0,36.0,4000,720.0,10.0,1,45,3000,0,0,1,0,1,0,Yes
28
+ 0,1500,1000,1,30.0,3500,560.0,10.0,1,44,4000,0,0,1,0,1,0,No
29
+ 1,2000,1500,1,60.0,3140,600.0,15.0,1,31,1500,1,0,1,1,1,0,No
30
+ 0,40000,40000,0,60.0,100000,15000.0,6.0,1,42,7000,0,1,1,1,3,1,Yes
31
+ 1,3000,3000,0,60.0,10000,800.0,7.0,1,47,1000,0,0,1,0,1,0,Yes
32
+ 0,500,500,0,15.0,7000,680.0,4.0,1,23,1000,0,1,1,1,4,0,Yes
33
+ 1,3000,1000,1,30.0,6000,900.0,1.0,3,46,2000,0,0,0,1,4,0,No
34
+ 0,3000,3000,0,30.0,5000,450.0,3.0,2,34,4500,0,0,1,1,5,0,Yes
35
+ 1,7000,3000,1,12.0,1000,100.0,3.0,3,50,3000,1,0,0,1,4,0,No
36
+ 1,3000,3000,0,30.0,3700,400.0,3.0,1,45,8000,1,1,1,0,1,0,Yes
37
+ 1,3000,3000,0,36.0,5000,500.0,4.0,1,32,7000,0,0,1,1,4,0,Yes
38
+ 1,600,600,0,60.0,3000,400.0,15.0,1,45,3000,1,1,1,0,3,0,Yes
39
+ 1,12000,7000,1,,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
40
+ 1,5000,2000,1,30.0,4000,1400.0,4.0,1,48,3000,0,0,0,0,1,0,No
41
+ 1,7000,5000,1,,900,190.0,1.0,2,43,4000,0,1,0,0,4,0,No
42
+ 0,2000,1500,1,30.0,2450,749.0,2.0,1,25,1500,1,0,0,0,1,0,No
43
+ 0,1000,1000,0,30.0,2000,400.0,5.0,3,31,2000,0,0,0,1,5,0,Yes
44
+ 1,300,300,0,30.0,2000,350.0,4.0,1,45,1000,1,0,1,0,1,0,Yes
45
+ 1,7000,5000,1,60.0,5000,650.0,3.0,3,47,6000,1,1,0,0,4,0,No
46
+ 1,300,300,0,60.0,6000,500.0,20.0,1,45,6000,1,1,1,0,1,0,Yes
47
+ 1,9000,7000,1,,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
48
+ 0,1500,1500,0,60.0,3000,400.0,2.0,1,27,3000,0,0,1,1,5,0,Yes
49
+ 0,9000,8000,1,36.0,9000,700.0,3.0,3,55,9000,1,0,1,1,3,0,No
50
+ 1,1000,1000,0,30.0,2800,540.0,10.0,1,36,15000,1,0,1,0,1,0,Yes
51
+ 0,9000,8000,1,120.0,9000,700.0,3.0,3,55,9000,1,0,1,1,3,0,No
52
+ 1,800,800,0,36.0,5000,400.0,3.0,1,35,2000,0,0,0,1,4,0,Yes
53
+ 1,5000,5000,0,30.0,1000,180.0,4.0,4,40,7000,0,0,1,1,3,1,Yes
54
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
55
+ 1,9000,8000,1,60.0,9000,600.0,4.0,4,49,9000,1,1,0,1,4,0,No
56
+ 1,30000,30000,0,60.0,10000,500.0,1.0,1,45,80000,0,0,1,1,5,0,Yes
57
+ 1,500,500,0,24.0,1000,200.0,2.0,2,35,700,0,0,1,1,4,0,Yes
58
+ 1,8000,8000,0,120.0,2800,300.0,11.0,2,49,9000,1,0,1,0,2,0,Yes
59
+ 0,10000,8000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,No
60
+ 0,2500,1300,1,60.0,1300,180.0,9.0,1,43,2000,1,0,1,0,1,0,No
61
+ 1,1000,1000,0,12.0,3000,100.0,25.0,1,59,3000,0,0,1,1,1,0,Yes
62
+ 0,17000,10000,1,36.0,4000,450.0,15.0,1,40,4000,0,0,1,0,1,0,No
63
+ 1,9000,5000,1,60.0,8000,250.0,2.0,2,39,6000,1,1,1,0,2,0,No
64
+ 1,700,600,1,20.0,1200,180.0,2.0,1,26,9700,0,0,0,1,4,0,No
65
+ 0,1000,1000,0,30.0,2600,490.0,8.0,3,43,3000,0,0,1,1,5,0,Yes
66
+ 1,12000,6000,1,30.0,10000,568.0,2.0,3,38,8000,1,1,0,0,4,0,No
67
+ 1,1000,1000,0,20.0,1600,230.0,3.0,1,45,2500,0,0,0,1,4,0,Yes
68
+ 0,300,300,0,30.0,3700,360.0,7.0,3,43,2000,0,0,1,1,4,0,Yes
69
+ 0,1500,1500,0,30.0,3000,350.0,2.0,3,37,4000,0,0,0,1,5,0,Yes
70
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
71
+ 0,1000,1000,0,30.0,3000,560.0,10.0,1,34,15000,0,0,1,0,1,0,Yes
72
+ 1,9000,6000,1,60.0,9000,1200.0,8.0,3,40,7000,1,1,0,1,4,0,No
73
+ 0,9000,6000,1,30.0,8000,800.0,2.0,4,33,8000,0,0,1,0,4,1,No
74
+ 0,20000,10000,1,60.0,20000,1000.0,1.0,3,40,9000,1,1,1,1,4,0,No
75
+ 1,10000,7000,1,60.0,8000,250.0,2.0,2,39,6000,1,1,0,0,2,0,No
76
+ 1,3000,3000,0,60.0,3210,760.0,7.0,1,27,1500,1,0,1,0,1,0,Yes
77
+ 0,300,300,0,60.0,1900,250.0,7.0,1,40,2000,0,0,0,0,1,0,Yes
78
+ 0,3000,3000,0,30.0,12000,1400.0,2.0,3,32,5000,0,1,1,1,3,1,Yes
79
+ 0,2500,2500,0,30.0,5000,550.0,3.0,1,39,5000,1,0,1,0,1,0,Yes
80
+ 1,1500,1500,0,24.0,3000,300.0,4.0,1,33,2000,0,0,0,0,1,0,Yes
81
+ 1,7000,7000,0,60.0,3000,500.0,3.0,3,31,8000,0,1,1,1,5,0,Yes
82
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,5000,0,1,1,1,2,0,No
83
+ 0,12000,5000,1,60.0,2000,0.0,0.0,3,39,7000,0,1,0,0,1,0,No
84
+ 0,10000,10000,0,30.0,25000,1400.0,6.0,3,50,12000,1,1,1,0,3,1,Yes
85
+ 1,10000,7000,1,30.0,9000,2000.0,4.0,3,34,8900,0,1,1,1,4,0,No
86
+ 0,600,500,1,60.0,600,125.0,12.0,1,59,2000,1,0,0,0,1,0,No
87
+ 0,10000,8000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,No
88
+ 0,1500,1200,1,60.0,2200,170.0,6.0,1,42,7000,0,0,0,0,1,0,No
89
+ 1,600,300,1,60.0,5000,680.0,20.0,3,45,5000,0,1,0,1,1,0,No
90
+ 1,3500,3500,0,60.0,5000,285.0,12.0,2,35,4000,1,0,1,0,3,0,Yes
91
+ 0,20000,20000,0,60.0,40000,2500.0,3.0,3,54,8000,1,1,0,0,3,1,Yes
92
+ 1,3000,3000,0,30.0,6000,200.0,2.5,1,37,3000,0,0,0,1,1,0,Yes
93
+ 0,6000,5000,1,60.0,12000,1250.0,8.0,1,29,4000,1,1,0,0,1,0,No
94
+ 1,10000,7000,1,60.0,8000,250.0,2.0,2,39,6000,1,1,0,0,2,0,No
95
+ 0,9000,9000,0,30.0,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,Yes
96
+ 1,8000,8000,0,36.0,2800,300.0,5.0,2,49,9000,1,0,1,0,2,0,Yes
97
+ 0,9000,9000,0,30.0,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,Yes
98
+ 1,1200,1200,0,30.0,1500,155.0,7.0,1,39,1000,0,0,1,0,1,0,Yes
99
+ 0,300,300,0,60.0,4300,400.0,9.0,1,44,3000,0,0,0,0,1,0,Yes
100
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
101
+ 1,1000,1000,0,30.0,1000,350.0,1.0,3,36,3000,0,0,0,1,4,0,Yes
102
+ 0,7000,5500,1,30.0,7000,400.0,5.0,2,45,5000,0,0,0,1,4,0,No
103
+ 1,3000,3000,0,36.0,5000,500.0,4.0,1,39,7000,0,0,0,1,5,0,Yes
104
+ 0,5000,5000,0,30.0,8500,500.0,5.0,2,43,7000,0,0,1,1,3,0,Yes
105
+ 0,9000,9000,0,30.0,10000,900.0,3.0,3,35,9000,0,0,0,1,4,1,Yes
106
+ 0,7000,7000,0,60.0,15000,459.0,5.0,1,49,13000,0,0,1,1,5,0,Yes
107
+ 1,1000,1000,0,30.0,7000,800.0,11.0,1,44,3000,1,0,1,0,1,0,Yes
108
+ 0,12000,10000,1,30.0,10700,320.0,4.0,2,38,10000,1,1,1,1,3,0,No
109
+ 1,3000,3000,0,30.0,9500,1000.0,6.0,1,40,800,0,0,1,0,1,0,Yes
110
+ 0,300,300,0,30.0,3000,30.0,1.0,2,28,3000,0,0,1,0,1,0,Yes
111
+ 0,300,300,0,30.0,10000,1800.0,6.0,2,35,1800,0,1,0,0,1,0,Yes
112
+ 1,6000,6000,0,60.0,9500,900.0,7.0,2,28,9000,0,1,1,1,3,0,Yes
113
+ 0,3000,2000,1,30.0,4000,500.0,4.0,1,32,3500,0,0,1,1,4,0,No
114
+ 0,2000,2000,0,30.0,12000,1200.0,2.0,3,40,4000,0,1,0,0,3,1,Yes
115
+ 1,2000,2000,0,60.0,3000,700.0,3.0,1,34,1000,0,0,1,0,1,0,Yes
116
+ 1,10000,7000,1,60.0,9000,600.0,4.0,4,49,9000,1,1,0,1,4,0,No
117
+ 1,600,600,0,60.0,7000,550.0,8.0,1,46,2000,0,0,1,1,5,0,Yes
118
+ 0,10000,7000,1,30.0,4000,400.0,8.0,4,60,9000,1,0,0,1,4,1,No
119
+ 0,2000,2000,0,60.0,60000,1400.0,4.0,2,35,60000,0,0,1,0,1,0,Yes
120
+ 0,10000,10000,0,60.0,40000,7000.0,3.0,1,49,8000,0,1,1,0,3,1,Yes
121
+ 0,500,500,0,60.0,3500,200.0,23.0,2,53,2600,1,0,1,1,4,0,Yes
122
+ 1,1000,1000,0,36.0,2000,310.0,3.0,1,44,2000,0,0,0,0,1,0,Yes
123
+ 0,2500,2200,1,30.0,5350,950.0,4.0,1,38,3000,1,0,0,0,1,0,No
124
+ 0,4000,4000,0,30.0,7000,1300.0,4.0,1,44,1000,0,0,1,1,4,0,Yes
125
+ 1,600,600,0,60.0,1000,190.0,1.0,3,26,1000,0,1,1,0,1,0,Yes
126
+ 1,3000,2800,1,30.0,5000,550.0,6.0,1,40,4000,0,1,1,1,4,0,No
127
+ 1,1000,1000,0,30.0,4000,457.0,8.0,1,52,8000,0,0,0,1,1,0,Yes
128
+ 1,3000,3000,0,30.0,5300,400.0,3.0,2,39,5000,0,0,1,1,5,0,Yes
129
+ 0,900,900,0,30.0,900,100.0,4.0,3,40,7000,0,0,1,0,5,0,Yes
130
+ 0,3000,2000,1,30.0,6000,200.0,10.0,1,35,7000,1,0,0,0,1,0,No
131
+ 0,3000,1000,1,30.0,9000,800.0,3.0,1,44,1000,1,1,1,0,1,0,No
132
+ 0,9000,6000,1,30.0,8000,800.0,2.0,4,33,8000,0,0,1,0,4,1,No
133
+ 0,400,400,0,60.0,2800,370.0,3.0,2,30,3000,0,0,0,1,4,0,Yes
134
+ 0,500,500,0,60.0,2600,400.0,16.0,2,53,2800,0,0,1,0,5,0,Yes
135
+ 1,9000,6000,1,60.0,9000,1200.0,8.0,3,40,7000,0,1,0,1,4,0,No
136
+ 1,3500,3500,0,15.0,5500,550.0,3.0,1,38,2000,1,0,1,0,1,0,Yes
137
+ 0,2000,1500,1,60.0,2800,300.0,2.0,1,43,3000,0,0,0,1,1,0,No
138
+ 1,1500,1500,0,30.0,700,180.0,3.0,3,30,2000,1,0,0,0,5,0,Yes
139
+ 0,3000,3000,0,60.0,15000,1000.0,15.0,3,40,1500,1,0,1,1,2,0,Yes
140
+ 1,2000,2000,0,30.0,2000,700.0,1.0,3,35,3000,0,0,1,1,4,0,Yes
141
+ 1,600,600,0,60.0,2000,500.0,2.0,3,26,2000,0,0,0,1,1,0,Yes
142
+ 1,400,400,0,30.0,4000,500.0,4.0,1,33,100,1,0,1,1,4,0,Yes
143
+ 1,700,700,0,12.0,1500,318.0,9.0,1,38,20000,0,0,0,0,1,0,Yes
144
+ 0,9000,6000,1,,8000,800.0,2.0,4,33,8000,0,0,1,0,4,1,No
145
+ 1,10000,7000,1,60.0,8000,250.0,2.0,2,39,6000,1,1,1,0,2,0,No
146
+ 1,2000,2000,0,30.0,2500,680.0,1.0,2,32,3000,1,0,1,0,3,0,Yes
147
+ 0,3000,3000,0,30.0,5000,300.0,5.0,2,36,4000,0,0,0,1,3,0,Yes
148
+ 0,10000,10000,0,60.0,300000,7000.0,2.0,3,52,9000,0,1,1,1,3,1,Yes
149
+ 0,1000,1000,0,30.0,4500,550.0,9.0,2,47,6500,1,0,1,1,4,0,Yes
150
+ 1,4000,4000,0,30.0,10000,3600.0,4.0,1,43,6000,1,1,0,0,1,1,Yes
151
+ 0,5000,5000,0,30.0,11000,1000.0,9.0,1,27,1500,0,0,1,1,5,0,Yes
152
+ 1,1500,1500,0,30.0,7000,150.0,4.0,2,33,7000,0,0,1,0,1,0,Yes
153
+ 1,1000,900,1,20.0,1800,225.0,2.0,1,48,8000,1,0,0,0,1,0,No
154
+ 0,5000,5000,0,30.0,12000,500.0,20.0,2,52,7000,0,0,1,1,3,0,Yes
155
+ 0,20000,10000,1,60.0,5000,100.0,1.0,2,30,9000,1,0,0,1,4,0,No
156
+ 1,3000,3000,0,30.0,6000,720.0,2.0,1,50,1100,0,0,0,1,4,0,Yes
157
+ 0,500,500,0,36.0,2000,210.0,3.0,1,25,2500,0,0,0,0,1,0,Yes
158
+ 0,10000,10000,0,36.0,4000,350.0,10.0,3,35,4000,1,0,1,0,1,0,Yes
159
+ 1,600,600,0,36.0,1200,200.0,4.0,1,28,2000,0,0,1,1,5,0,Yes
160
+ 1,1200,1200,0,30.0,3700,500.0,5.0,1,35,3000,0,0,1,0,5,0,Yes
161
+ 0,4000,3000,1,60.0,70000,2800.0,4.0,1,43,7000,1,1,0,1,3,1,No
162
+ 1,800,800,0,60.0,4000,200.0,15.0,1,40,4000,0,1,1,0,4,0,Yes
163
+ 1,3000,2000,1,30.0,5500,870.0,7.0,1,32,20000,1,0,1,0,1,0,No
164
+ 1,1500,1000,1,30.0,2000,230.0,3.0,1,50,2000,0,0,1,0,1,0,No
165
+ 1,3000,1500,1,30.0,5000,750.0,6.0,1,32,2000,0,0,0,0,3,0,No
166
+ 1,10000,8000,1,30.0,4600,350.0,2.0,2,29,10000,0,0,0,1,1,0,No
167
+ 1,2500,2000,1,60.0,5600,600.0,4.0,1,31,1500,0,1,1,0,1,0,No
168
+ 1,500,500,0,60.0,2000,280.0,4.0,1,29,2000,1,1,1,1,4,0,Yes
169
+ 1,500,500,0,15.0,1500,312.0,6.0,1,24,20000,0,0,1,0,1,0,Yes
170
+ 1,2000,2000,0,60.0,2000,580.0,2.0,3,32,2000,1,0,0,1,4,0,Yes
171
+ 0,7000,5500,1,30.0,7000,400.0,5.0,2,45,5000,0,0,0,1,4,0,No
172
+ 0,5000,5000,0,30.0,10000,1800.0,1.0,1,46,1000,0,0,0,1,1,0,Yes
173
+ 0,9000,6000,1,30.0,8000,800.0,2.0,4,33,8000,0,0,1,0,4,1,No
174
+ 1,400,400,0,15.0,8000,600.0,4.0,1,46,4000,0,0,0,0,1,0,Yes
175
+ 0,5000,5000,0,30.0,14000,1300.0,3.0,1,37,1200,0,0,0,1,5,0,Yes
176
+ 0,300,300,0,60.0,5200,530.0,19.0,2,50,1500,0,0,0,0,1,0,Yes
177
+ 1,1000,1000,0,60.0,5000,400.0,18.0,2,43,5000,0,1,0,0,4,0,Yes
178
+ 1,3000,3000,0,30.0,4000,1500.0,7.0,2,37,4000,1,0,1,1,3,0,Yes
179
+ 1,1500,1500,0,30.0,3000,360.0,2.0,1,24,1000,0,0,1,0,1,0,Yes
180
+ 1,500,500,0,60.0,2000,150.0,5.0,1,30,2000,0,1,1,0,3,0,Yes
181
+ 1,12000,10000,1,30.0,9000,490.0,4.0,3,34,9000,0,1,1,1,4,0,No
182
+ 1,3000,10000,1,30.0,8000,900.0,2.0,1,38,4000,1,0,1,1,5,0,No
183
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
184
+ 0,3000,3000,0,60.0,10000,164.0,3.0,1,36,10000,1,0,0,1,1,0,Yes
185
+ 1,1000,800,1,36.0,2000,192.0,2.0,1,27,1000,0,0,0,0,1,0,No
186
+ 1,10000,7000,1,60.0,10000,470.0,2.0,3,33,8000,1,0,0,1,4,0,No
187
+ 1,5000,3000,1,20.0,6000,600.0,1.0,3,33,6000,1,0,0,0,1,0,No
188
+ 1,7000,5000,1,60.0,3300,370.0,9.0,2,38,7000,1,0,0,0,4,0,No
189
+ 0,30000,15000,1,30.0,3600,250.0,1.0,2,40,12000,0,1,1,0,1,0,No
190
+ 1,2000,2000,0,30.0,4000,700.0,7.0,2,25,10000,0,0,0,1,3,0,Yes
191
+ 1,1200,1070,1,60.0,2000,250.0,5.0,1,38,8000,0,0,0,1,1,0,No
192
+ 1,1000,1000,0,30.0,2000,700.0,3.0,3,37,2000,0,0,1,1,4,0,Yes
193
+ 0,20000,10000,1,60.0,50000,4000.0,4.0,1,47,11000,0,1,1,1,3,1,No
194
+ 0,2000,2000,0,20.0,4000,500.0,2.0,1,21,2500,0,0,1,0,1,0,Yes
195
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
196
+ 1,6000,5000,1,36.0,1000,355.0,2.0,1,23,20000,0,0,1,1,4,0,No
197
+ 1,4000,4000,0,60.0,13000,3000.0,3.0,1,33,9000,0,1,0,1,3,1,Yes
198
+ 1,8000,8000,0,60.0,4000,450.0,3.0,3,43,7000,0,0,1,0,3,0,Yes
199
+ 0,7000,7000,0,36.0,3000,250.0,13.0,1,38,3000,0,0,1,0,1,0,Yes
200
+ 1,600,600,0,15.0,1000,300.0,7.0,1,36,4000,1,0,0,1,5,0,Yes
201
+ 1,10000,7000,1,60.0,8000,250.0,2.0,2,39,6000,1,1,1,0,2,0,No
202
+ 0,9000,8000,1,36.0,9000,700.0,3.0,3,55,9000,1,0,1,1,3,0,No
203
+ 0,8000,7000,1,36.0,5000,4000.0,2.0,3,39,9700,0,1,1,1,4,0,No
204
+ 1,6000,6000,0,36.0,7000,550.0,8.0,1,35,2000,1,0,1,1,4,0,Yes
205
+ 1,1000,870,1,30.0,900,180.0,9.0,1,40,3000,0,0,0,1,1,0,No
206
+ 1,500,500,0,60.0,5400,500.0,20.0,3,42,3200,0,0,1,1,4,0,Yes
207
+ 1,1000,1000,0,30.0,4800,562.0,8.0,1,33,20000,0,0,1,0,1,0,Yes
208
+ 0,1000,1000,0,60.0,1000,120.0,3.0,1,34,6000,1,0,0,0,1,0,Yes
209
+ 0,1200,1000,1,12.0,1800,190.0,5.0,1,50,1000,0,0,0,1,1,0,No
210
+ 1,600,300,1,60.0,1000,150.0,15.0,3,40,1000,0,1,0,1,1,0,No
211
+ 0,10000,10000,0,36.0,20000,165.0,9.0,2,45,15000,0,0,1,0,3,0,Yes
212
+ 1,1500,1500,0,50.0,1000,125.0,6.0,3,54,2000,0,0,1,1,4,0,Yes
213
+ 0,10000,8000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,No
214
+ 1,10000,8000,1,60.0,1000,113.5,3.0,3,32,7000,1,1,1,0,4,0,No
215
+ 0,1000,1000,0,30.0,2180,227.0,10.0,1,46,1500,0,0,1,0,1,0,Yes
216
+ 0,2000,2000,0,36.0,6500,860.0,13.0,1,33,15000,0,0,1,0,1,0,Yes
217
+ 0,3000,3000,0,15.0,5000,450.0,4.0,1,39,5000,0,0,1,0,2,0,Yes
218
+ 0,500,500,0,24.0,1000,200.0,2.0,1,29,1500,0,0,1,0,1,0,Yes
219
+ 0,2000,2000,0,30.0,14000,3000.0,4.0,1,38,8000,0,1,1,1,5,1,Yes
220
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
221
+ 1,500,500,0,60.0,1900,165.0,5.0,3,40,2000,0,0,1,1,4,0,Yes
222
+ 1,600,600,0,30.0,1000,180.0,7.0,1,25,700,1,0,1,1,1,0,Yes
223
+ 1,700,700,0,24.0,1400,140.0,1.0,1,40,3000,0,0,0,1,4,0,Yes
224
+ 0,1800,1500,1,30.0,2500,278.0,4.0,3,38,2000,0,0,1,0,1,0,No
225
+ 1,4000,4000,0,30.0,3250,400.0,9.0,2,44,5000,1,1,1,1,4,0,Yes
226
+ 1,450,450,1,60.0,7000,120.0,3.0,1,27,600,0,0,1,0,1,0,Yes
227
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
228
+ 1,9000,6000,1,60.0,9000,1200.0,8.0,3,40,7000,1,1,0,1,4,0,No
229
+ 1,9000,6000,1,30.0,1000,3000.0,2.0,3,38,7000,1,1,0,0,3,0,No
230
+ 0,7000,5000,1,60.0,40000,6000.0,3.0,3,44,7000,0,1,1,1,3,1,No
231
+ 1,600,600,0,60.0,2000,200.0,18.0,1,43,2000,0,1,1,0,1,0,Yes
232
+ 1,2000,2000,0,60.0,2000,620.0,1.0,2,37,2000,0,0,1,0,3,0,Yes
233
+ 1,7000,5000,1,60.0,5000,650.0,3.0,3,47,6000,1,1,1,0,4,0,No
234
+ 1,1000,1000,0,30.0,1200,125.0,2.0,2,41,2000,0,0,0,0,3,0,Yes
235
+ 1,9000,6000,1,60.0,9000,1200.0,8.0,3,40,7000,1,1,0,1,4,0,No
236
+ 1,1000,800,1,20.0,3000,800.0,1.0,1,56,3500,0,0,1,0,1,0,No
237
+ 1,4000,4000,0,30.0,8000,1000.0,4.0,1,20,2260,0,0,1,1,4,0,Yes
238
+ 0,10000,7000,1,30.0,4000,400.0,8.0,4,60,9000,1,0,0,1,4,1,No
239
+ 0,900,800,1,12.0,2000,250.0,3.0,2,41,5000,0,0,0,0,3,0,No
240
+ 1,600,510,1,60.0,6000,700.0,3.0,1,35,7000,0,0,0,1,1,0,No
241
+ 0,25000,20000,1,36.0,10000,5000.0,20.0,3,45,10000,1,0,0,1,4,0,No
242
+ 0,1000,1000,1,30.0,1500,256.0,4.0,2,22,2000,0,0,0,0,1,0,Yes
243
+ 0,4000,4000,0,30.0,6000,277.0,4.0,2,43,8000,1,0,0,0,3,0,Yes
244
+ 1,10000,10000,0,36.0,12000,1300.0,3.0,1,32,9000,0,0,0,0,3,0,Yes
245
+ 1,2000,2000,0,60.0,6000,670.0,7.0,1,45,3000,0,0,0,0,1,0,Yes
246
+ 1,2000,1000,1,15.0,2000,150.0,2.0,1,41,2000,0,0,0,1,1,0,No
247
+ 0,12000,10000,1,60.0,4500,320.0,6.0,2,50,30000,0,0,1,0,3,0,No
248
+ 0,15000,8000,1,30.0,3600,2500.0,5.0,2,30,9500,0,1,1,0,4,0,No
249
+ 0,10000,10000,0,60.0,5000,700.0,8.0,1,36,23000,0,0,0,0,1,0,Yes
250
+ 0,300,300,0,60.0,2400,300.0,8.0,3,46,3000,0,0,1,1,1,0,Yes
251
+ 1,1500,1000,1,30.0,4000,250.0,3.0,1,26,2500,0,1,0,0,1,0,No
252
+ 1,2000,1000,1,15.0,3000,100.0,6.0,3,37,4500,0,0,0,1,5,0,No
253
+ 1,5000,5000,0,30.0,6000,900.0,8.0,1,36,1500,1,0,0,0,1,0,Yes
254
+ 1,3500,3000,1,30.0,7000,720.0,3.0,1,38,1000,0,0,0,1,4,0,No
255
+ 1,8000,8000,0,60.0,4000,450.0,3.0,3,43,7000,0,0,1,0,3,0,Yes
256
+ 0,5000,5000,0,60.0,8000,580.0,5.0,3,39,5000,1,0,0,1,3,0,Yes
257
+ 1,2000,2000,0,15.0,3500,300.0,5.0,1,36,4000,0,0,1,1,5,0,Yes
258
+ 1,1000,1000,0,60.0,1000,400.0,1.0,1,39,2000,1,0,0,0,1,0,Yes
259
+ 1,500,500,0,30.0,5000,160.0,6.0,3,48,1800,0,0,1,1,5,0,Yes
260
+ 0,2200,2200,0,30.0,5000,560.0,5.0,3,53,1800,0,1,0,1,4,0,Yes
261
+ 1,1000,1000,0,24.0,2500,350.0,12.0,3,55,1500,1,0,0,1,4,0,Yes
262
+ 0,3000,3000,0,40.0,3000,750.0,7.0,1,28,3000,1,0,1,0,1,0,Yes
263
+ 0,1000,1000,0,60.0,7000,540.0,1.0,1,27,5000,0,1,1,1,5,1,Yes
264
+ 0,9000,9000,0,30.0,5000,320.0,9.0,4,38,9000,1,1,1,1,1,1,Yes
265
+ 0,10000,10000,0,50.0,14000,850.0,4.0,1,45,10000,1,0,0,1,1,0,Yes
266
+ 0,3000,1500,1,30.0,4500,730.0,4.0,1,34,15000,1,0,1,0,1,0,No
267
+ 1,1200,1000,1,30.0,5000,600.0,10.0,1,32,5000,0,0,0,0,5,0,No
268
+ 0,800,400,1,15.0,1200,120.0,2.0,1,25,1120,0,1,1,0,1,0,No
269
+ 0,1500,1500,0,30.0,3200,548.0,5.0,1,31,3000,0,0,1,0,1,0,Yes
270
+ 1,300,300,0,15.0,5000,450.0,4.0,1,53,5000,0,0,0,0,1,0,Yes
271
+ 1,2000,2000,0,30.0,2500,560.0,1.0,2,34,2000,0,0,1,0,3,0,Yes
272
+ 1,2000,2000,0,30.0,4000,480.0,4.0,1,39,2500,0,0,1,1,1,0,Yes
273
+ 0,1000,1000,0,30.0,2420,499.0,7.0,1,28,2000,0,1,0,0,1,0,Yes
274
+ 0,1000,1000,0,30.0,8000,1000.0,5.0,1,30,1000,0,1,1,0,1,0,Yes
275
+ 0,2000,1500,1,20.0,3000,450.0,2.0,1,25,5000,0,0,1,0,1,0,No
276
+ 1,300,300,0,15.0,7000,450.0,5.0,1,33,4500,0,0,1,0,1,0,Yes
277
+ 0,2000,2000,0,60.0,3300,385.0,18.0,1,40,1500,1,0,0,1,1,0,Yes
278
+ 1,6000,6000,0,60.0,4600,500.0,4.0,2,41,2000,0,0,1,0,1,0,Yes
279
+ 1,12000,7000,1,30.0,9000,700.0,4.0,3,34,9000,0,1,0,1,4,0,No
280
+ 1,5000,5000,0,30.0,9000,900.0,12.0,1,36,1200,1,0,0,0,1,0,Yes
281
+ 0,20000,15000,1,36.0,15000,8000.0,6.0,3,51,9000,0,1,1,1,3,1,No
282
+ 0,500,200,1,36.0,1000,140.0,1.0,1,33,5000,0,0,0,1,4,0,No
283
+ 0,2000,2000,0,30.0,5000,880.0,8.0,1,28,15000,1,0,1,0,1,0,Yes
284
+ 0,2000,2000,0,30.0,4000,400.0,1.0,2,35,4000,0,0,0,1,5,0,Yes
285
+ 0,9000,9000,0,30.0,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,Yes
286
+ 1,500,500,0,60.0,2500,240.0,5.0,1,30,2500,0,1,0,0,1,0,Yes
287
+ 0,4000,4000,0,30.0,10000,600.0,5.0,2,43,7000,0,0,1,0,3,0,Yes
288
+ 0,10000,8000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,No
289
+ 1,4000,2000,1,30.0,5000,850.0,1.0,3,42,3000,0,0,1,1,4,0,No
290
+ 1,3000,3000,0,12.0,5000,550.0,5.0,3,29,1800,0,0,1,1,4,0,Yes
291
+ 1,3000,3000,0,30.0,6000,1400.0,1.0,1,46,5000,0,0,1,0,1,0,Yes
292
+ 1,400,365,1,12.0,4000,800.0,5.0,1,44,6000,0,0,0,1,1,0,No
293
+ 0,2500,2000,1,30.0,5000,300.0,6.0,2,36,2000,0,0,0,0,3,0,No
294
+ 0,1500,1500,0,30.0,3000,100.0,3.0,1,42,1500,0,0,0,0,1,0,Yes
295
+ 1,5000,2000,1,60.0,3000,1200.0,5.0,1,43,3000,0,0,1,1,5,0,No
296
+ 0,3000,3000,0,15.0,2000,360.0,3.0,2,43,4000,1,0,1,1,4,0,Yes
297
+ 0,19000,19000,0,60.0,25000,356.0,5.0,1,63,40000,1,0,1,0,2,0,Yes
298
+ 0,7000,5000,1,30.0,1300,170.0,5.0,2,45,5000,0,0,1,1,4,0,No
299
+ 1,500,500,0,12.0,1500,315.0,6.0,1,37,20000,0,0,1,0,1,0,Yes
300
+ 1,500,500,0,30.0,3100,300.0,6.0,2,31,2600,0,0,1,0,1,0,Yes
301
+ 1,20000,10000,1,30.0,10700,3000.0,4.0,2,38,10000,1,1,1,1,3,0,No
302
+ 0,8000,8000,0,60.0,12000,4000.0,6.0,3,34,9000,0,1,1,1,3,1,Yes
303
+ 1,25000,20000,1,36.0,10000,900.0,25.0,1,50,10000,1,0,1,0,1,0,No
304
+ 0,300,300,0,15.0,4000,250.0,5.0,2,38,2500,0,1,0,0,3,0,Yes
305
+ 1,6000,6000,0,60.0,9500,900.0,7.0,2,28,9000,1,1,1,1,3,0,Yes
306
+ 0,2000,2000,0,60.0,2500,263.0,5.0,3,35,2000,1,0,1,1,5,0,Yes
307
+ 0,10000,8000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,No
308
+ 1,3500,3500,0,40.0,4800,420.0,9.0,2,27,5000,0,0,0,1,5,0,Yes
309
+ 0,2000,2000,0,30.0,8000,740.0,4.0,1,25,4000,0,1,1,0,3,0,Yes
310
+ 0,5000,5000,0,60.0,9000,1200.0,10.0,1,47,1500,1,0,0,0,1,0,Yes
311
+ 1,7000,7000,0,30.0,30000,500.0,3.0,3,31,8000,0,0,1,1,5,0,Yes
312
+ 0,1000,1000,0,30.0,2000,450.0,8.0,2,45,4000,0,0,1,1,5,0,Yes
313
+ 1,300,300,0,30.0,5600,500.0,3.0,3,39,3000,1,0,1,1,4,0,Yes
314
+ 1,700,700,0,15.0,2000,700.0,2.0,1,40,5000,0,0,0,0,1,0,Yes
315
+ 0,1500,1500,0,60.0,10000,9000.0,1.0,1,35,6000,1,1,1,1,5,1,Yes
316
+ 0,2000,2000,0,60.0,2000,450.0,6.0,3,26,2000,0,0,1,1,5,0,Yes
317
+ 1,500,200,1,20.0,4000,500.0,4.0,1,40,2000,0,0,0,0,1,0,No
318
+ 1,5000,5000,0,15.0,7000,780.0,1.0,1,42,4500,0,0,1,0,3,0,Yes
319
+ 0,5000,5000,0,60.0,10000,256.0,5.0,2,36,12000,1,0,1,0,3,0,Yes
320
+ 0,9000,9000,0,30.0,5000,320.0,9.0,4,38,9000,0,1,1,1,1,1,Yes
321
+ 1,2000,1500,1,30.0,3000,200.0,5.0,1,35,1000,0,0,1,1,4,0,No
322
+ 0,7000,7000,0,30.0,11000,4000.0,2.0,3,39,12500,0,1,1,1,4,0,Yes
323
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
324
+ 1,500,500,0,15.0,7000,860.0,1.0,3,26,800,0,1,0,0,1,0,Yes
325
+ 0,2000,2000,0,30.0,4000,460.0,5.0,3,33,6000,0,0,0,0,5,0,Yes
326
+ 0,10000,7000,1,30.0,20000,14000.0,5.0,3,43,6000,0,1,1,1,3,1,No
327
+ 1,8000,8000,0,60.0,4000,450.0,3.0,3,43,7000,0,0,1,0,3,0,Yes
328
+ 1,6000,6000,0,30.0,8000,545.0,5.0,1,38,3000,1,0,0,0,1,0,Yes
329
+ 0,2000,2000,0,30.0,6000,560.0,7.0,3,32,2000,0,0,1,1,5,0,Yes
330
+ 0,1500,1000,1,30.0,1000,120.0,3.0,3,33,6000,0,1,0,0,5,0,No
331
+ 0,3000,2000,1,30.0,4000,825.0,6.0,1,37,15000,0,0,0,1,4,0,No
332
+ 1,1000,1000,0,60.0,5000,590.0,4.0,2,29,12000,0,0,1,0,1,0,Yes
333
+ 0,8000,7000,1,,5000,4000.0,2.0,3,39,9000,0,1,1,1,4,0,No
334
+ 1,300,300,0,60.0,5000,500.0,4.0,1,36,7000,0,0,1,1,1,0,Yes
335
+ 0,9000,9000,0,30.0,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,Yes
336
+ 1,1000,1000,0,60.0,4000,288.0,4.0,1,27,2000,0,0,0,1,1,0,Yes
337
+ 1,2000,2000,0,30.0,3800,300.0,2.0,2,28,3800,0,0,0,0,2,0,Yes
338
+ 1,1500,1500,0,60.0,6850,700.0,7.0,1,40,4000,0,1,1,1,1,0,Yes
339
+ 0,1000,800,1,30.0,1600,190.0,4.0,1,38,4000,1,0,1,1,4,0,No
340
+ 0,3000,2500,1,30.0,6000,625.0,5.0,1,34,6000,0,0,1,0,1,0,No
341
+ 0,800,500,1,30.0,1500,500.0,4.0,1,36,1000,1,0,0,0,1,0,No
342
+ 0,2000,2000,0,60.0,20000,1800.0,1.0,3,37,5000,0,1,0,1,5,1,Yes
343
+ 0,850,850,0,60.0,5000,200.0,0.0,3,35,3500,1,0,0,1,5,0,Yes
344
+ 1,5000,4000,1,60.0,8000,842.0,7.0,1,42,6000,1,1,0,0,1,0,No
345
+ 1,2000,2000,0,30.0,1400,273.0,5.0,1,28,2000,1,0,1,1,1,0,Yes
346
+ 1,2000,2000,1,60.0,3800,400.0,3.0,1,56,1800,0,0,1,0,1,0,Yes
347
+ 1,500,500,0,30.0,2800,400.0,27.0,1,48,3000,1,0,1,0,1,0,Yes
348
+ 1,2000,2000,0,30.0,8600,507.0,10.0,1,32,1500,0,0,1,0,1,0,Yes
349
+ 1,7000,7000,0,30.0,3600,2000.0,1.0,2,40,2000,0,1,1,0,5,0,Yes
350
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
351
+ 1,1000,1000,0,30.0,5600,386.0,10.0,1,38,1500,0,0,0,0,1,0,Yes
352
+ 1,800,800,0,30.0,4000,60.0,12.0,1,36,4000,0,0,0,1,1,0,Yes
353
+ 0,5000,5000,0,60.0,9000,1200.0,15.0,1,47,1000,1,0,1,1,1,0,Yes
354
+ 1,10000,7000,1,30.0,9000,2000.0,4.0,3,34,8900,0,1,1,1,4,0,No
355
+ 1,3000,2000,1,60.0,5000,856.0,5.0,1,30,4000,0,0,0,0,1,0,No
356
+ 0,2500,2500,0,60.0,17000,1400.0,5.0,3,40,8000,1,1,1,1,5,1,Yes
357
+ 0,3000,3000,0,30.0,2600,576.0,2.0,1,36,5000,0,0,0,1,1,0,Yes
358
+ 0,7000,5500,1,,7000,400.0,5.0,2,45,5000,0,0,1,1,4,0,No
359
+ 1,7000,5000,1,60.0,16000,9000.0,3.0,1,39,10000,1,1,0,1,3,1,No
360
+ 1,1500,1500,0,30.0,2200,390.0,3.0,1,25,1500,0,0,0,0,1,0,Yes
361
+ 1,500,500,0,20.0,1000,250.0,3.0,1,53,1000,0,0,1,1,4,0,Yes
362
+ 0,500,500,0,30.0,5100,400.0,6.0,2,35,4000,0,0,1,1,5,0,Yes
363
+ 1,600,600,0,30.0,1000,150.0,5.0,1,25,700,0,0,1,0,1,0,Yes
364
+ 1,2000,2000,0,30.0,1000,300.0,6.0,1,30,5000,0,0,1,1,5,0,Yes
365
+ 1,500,500,0,25.0,4200,560.0,3.0,1,20,700,0,0,1,0,1,0,Yes
366
+ 1,600,600,0,12.0,1200,360.0,5.0,1,41,20000,0,0,1,0,1,0,Yes
367
+ 1,400,400,0,60.0,6200,550.0,15.0,3,56,1300,1,0,0,1,4,0,Yes
368
+ 0,800,500,1,60.0,15000,450.0,2.0,3,54,1500,0,1,0,1,1,1,No
369
+ 1,5000,3000,1,36.0,3000,1500.0,4.0,2,46,2000,0,0,1,0,1,0,No
370
+ 1,1000,1000,0,15.0,2000,100.0,3.0,1,30,5000,0,0,1,0,1,0,Yes
371
+ 1,800,800,0,20.0,1600,216.0,3.0,1,40,4000,1,0,1,0,1,0,Yes
372
+ 0,1500,1300,1,30.0,2600,200.0,4.0,1,29,6000,0,0,0,0,1,0,No
373
+ 1,500,500,0,35.0,1000,600.0,4.0,3,28,10000,0,0,1,0,4,0,Yes
374
+ 0,5000,5000,0,60.0,4460,535.0,5.0,1,31,5000,1,0,1,1,1,0,Yes
375
+ 1,3000,2000,1,30.0,2300,552.0,6.0,1,28,3000,1,1,1,0,1,0,No
376
+ 0,5000,5000,0,30.0,10000,2000.0,2.0,3,48,8000,1,1,1,1,3,1,Yes
377
+ 1,4000,4000,0,30.0,9000,900.0,4.0,1,45,1000,0,0,0,0,1,0,Yes
378
+ 0,2500,2500,0,60.0,5000,570.0,4.0,2,38,1800,1,0,0,0,3,0,Yes
379
+ 1,9000,6000,1,60.0,9000,1200.0,8.0,3,40,7000,1,1,0,1,4,0,No
380
+ 1,200,200,0,30.0,5200,400.0,8.0,2,27,1000,0,0,0,1,5,0,Yes
381
+ 1,2000,2000,0,30.0,4000,300.0,5.0,1,41,4000,0,0,1,1,5,0,Yes
382
+ 1,3000,3000,0,30.0,9000,450.0,5.0,2,53,7000,0,0,0,1,3,0,Yes
383
+ 1,2500,2500,0,36.0,10000,700.0,5.0,1,30,8000,1,0,0,1,4,0,Yes
384
+ 1,7000,5000,1,60.0,5000,650.0,3.0,3,47,6000,1,1,1,0,4,0,No
385
+ 0,6000,6000,0,60.0,2310,6000.0,5.0,3,40,1000,1,0,1,1,4,0,Yes
386
+ 0,600,600,0,30.0,3000,365.0,2.0,3,30,2000,0,1,0,1,5,0,Yes
387
+ 1,1300,1300,0,20.0,2600,663.0,5.0,1,21,3000,0,0,1,1,4,0,Yes
388
+ 1,600,600,0,30.0,7000,500.0,8.0,1,45,2000,0,0,0,1,5,0,Yes
389
+ 0,3000,2000,1,15.0,3000,300.0,8.0,1,39,4500,0,0,0,1,5,0,No
390
+ 0,2000,2000,0,60.0,2000,155.0,8.0,3,35,2000,0,0,0,1,5,0,Yes
391
+ 1,2000,2000,0,30.0,2700,300.0,5.0,3,35,3000,0,0,1,1,4,0,Yes
392
+ 1,500,500,0,60.0,2000,250.0,15.0,1,40,2000,1,1,1,0,1,0,Yes
393
+ 0,15000,12000,1,60.0,15000,860.0,4.0,3,30,6000,0,0,1,1,4,0,No
394
+ 1,600,600,0,60.0,15000,700.0,4.0,3,47,5000,1,0,1,1,5,0,Yes
395
+ 1,1500,1500,0,30.0,4500,150.0,6.0,3,37,7000,0,0,1,1,5,0,Yes
396
+ 1,1000,1000,0,36.0,8000,800.0,3.0,1,34,3000,1,0,1,0,1,0,Yes
397
+ 1,5000,5000,0,30.0,5000,1500.0,4.0,1,45,1000,1,0,0,0,1,0,Yes
398
+ 1,1000,1000,0,30.0,8000,620.0,3.0,3,38,3620,0,1,1,1,4,0,Yes
399
+ 1,1500,1500,0,60.0,9500,573.0,5.0,1,34,5000,0,0,1,1,1,0,Yes
400
+ 0,3000,2000,1,30.0,4500,840.0,12.0,1,46,10000,0,0,1,1,4,0,No
401
+ 1,10000,8000,1,30.0,5000,3000.0,4.0,2,38,7000,1,1,1,1,3,0,No
402
+ 1,5000,5000,0,15.0,3400,400.0,3.0,2,33,6000,0,0,0,0,1,0,Yes
403
+ 0,9000,8000,1,24.0,9000,700.0,3.0,3,55,9000,1,0,1,1,3,0,No
404
+ 1,2500,2500,0,60.0,2000,280.0,0.0,3,30,5000,0,0,1,0,3,0,Yes
405
+ 1,2000,2000,0,36.0,9000,700.0,7.0,1,30,5000,1,0,1,0,1,0,Yes
406
+ 0,2000,2000,0,30.0,2200,230.0,1.0,1,27,3000,0,0,0,1,1,0,Yes
407
+ 1,1500,1000,1,30.0,1000,128.0,3.0,2,40,7000,1,0,0,0,3,0,No
408
+ 1,2000,2000,0,30.0,25000,1300.0,5.0,2,30,3500,0,0,1,1,3,0,Yes
409
+ 1,1000,600,1,15.0,6000,900.0,5.0,1,46,4000,0,0,1,1,1,0,No
410
+ 1,5000,5000,0,30.0,11500,1160.0,4.0,3,52,8000,0,1,1,1,5,0,Yes
411
+ 0,1000,1000,0,30.0,4000,313.0,5.0,3,41,2000,0,0,1,1,5,0,Yes
412
+ 1,1500,1000,1,30.0,3000,500.0,5.0,3,36,4500,0,0,1,0,5,0,No
413
+ 0,1000,1000,0,30.0,5000,165.0,7.0,1,45,1650,1,1,1,0,1,0,Yes
414
+ 0,5000,5000,0,30.0,8000,500.0,5.0,3,39,5000,1,0,1,0,3,0,Yes
415
+ 1,2000,2000,0,30.0,2000,750.0,1.0,3,30,3000,1,0,0,1,4,0,Yes
416
+ 1,7000,5000,1,60.0,5000,650.0,3.0,3,47,6000,1,1,1,0,4,0,No
417
+ 0,600,600,0,30.0,8000,600.0,3.0,3,28,6000,1,0,1,1,4,0,Yes
418
+ 0,1500,1500,0,50.0,3500,255.0,5.0,2,32,4100,0,0,0,0,3,0,Yes
419
+ 1,500,500,0,24.0,1000,120.0,1.0,2,25,1000,0,0,1,1,4,0,Yes
420
+ 1,2000,1500,1,30.0,2500,280.0,4.0,1,42,6000,0,0,0,1,1,0,No
421
+ 1,500,500,0,20.0,1000,225.0,3.0,1,51,1500,0,0,1,0,1,0,Yes
422
+ 1,8000,7000,1,36.0,2800,300.0,11.0,2,49,6000,1,0,1,0,2,0,No
423
+ 1,3000,1000,1,30.0,9000,1000.0,1.0,1,38,4000,1,0,0,1,5,0,No
424
+ 1,13000,10000,1,60.0,20000,100.0,1.0,3,40,9000,1,1,1,1,4,0,No
425
+ 0,8000,6000,1,30.0,10000,560.0,3.0,3,35,5000,1,0,0,1,4,1,No
426
+ 1,5000,5000,0,75.0,9000,980.0,4.0,1,34,1800,0,0,0,0,1,0,Yes
427
+ 1,1500,1000,0,30.0,3000,360.0,4.0,1,43,6000,1,0,0,0,1,0,No
428
+ 0,8000,5000,1,60.0,5000,400.0,1.0,2,30,5000,1,0,0,1,4,0,No
429
+ 0,2000,1500,1,20.0,3000,400.0,5.0,1,30,1800,0,0,0,1,1,0,No
430
+ 0,3000,3000,0,60.0,14000,1800.0,2.0,1,47,6000,0,1,0,1,5,1,Yes
431
+ 1,2500,2500,0,60.0,8000,850.0,9.0,1,41,3000,1,0,1,0,1,0,Yes
432
+ 1,500,500,0,50.0,5500,100.0,4.0,2,43,2000,0,0,1,0,1,0,Yes
433
+ 1,2000,800,1,12.0,1800,420.0,5.0,1,38,20000,0,0,1,0,1,0,No
434
+ 0,3000,3000,0,60.0,6570,746.0,4.0,1,42,5000,1,0,0,1,1,0,Yes
435
+ 0,1500,1500,0,30.0,2880,699.0,3.0,3,29,2000,0,0,1,1,5,0,Yes
436
+ 1,8000,7000,1,60.0,10000,4000.0,2.0,3,33,8000,0,0,0,1,4,0,No
437
+ 0,2000,2000,0,60.0,3550,515.0,2.0,1,32,3000,0,1,1,0,1,0,Yes
438
+ 0,10000,8000,1,30.0,4000,400.0,8.0,4,60,9000,1,0,1,1,4,1,No
439
+ 0,2000,2000,0,60.0,3000,500.0,5.0,1,45,3000,1,0,1,0,1,0,Yes
440
+ 1,2000,2000,0,60.0,3000,1120.0,1.0,3,32,4000,1,0,0,1,4,0,Yes
441
+ 0,5000,5000,0,60.0,6000,750.0,3.0,3,37,5000,0,0,0,1,5,0,Yes
442
+ 0,1600,1600,0,60.0,5000,285.0,3.0,3,48,4000,1,0,0,1,4,0,Yes
443
+ 1,600,600,0,60.0,2500,200.0,11.0,1,36,3000,0,1,0,0,1,0,Yes
444
+ 0,1000,1000,0,30.0,5000,250.0,3.0,1,28,2500,0,1,0,0,1,0,Yes
445
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
446
+ 0,3000,3000,0,30.0,6500,1030.0,2.0,1,32,5000,1,1,1,1,1,0,Yes
447
+ 0,2000,2000,0,60.0,3000,773.0,4.0,3,46,2000,0,0,1,1,5,0,Yes
448
+ 0,2000,2000,0,36.0,1000,800.0,28.0,1,53,1000,0,0,1,0,1,0,Yes
449
+ 0,8000,4000,1,60.0,9000,800.0,6.0,1,39,5000,1,0,1,0,1,0,No
450
+ 1,2000,2000,0,30.0,3000,520.0,3.0,2,34,1000,0,0,1,0,3,0,Yes
451
+ 1,1000,1000,0,15.0,2500,450.0,12.0,3,55,1500,0,0,0,1,4,0,Yes
452
+ 0,4000,4000,0,30.0,12000,6000.0,4.0,1,37,9000,0,1,0,0,3,1,Yes
453
+ 1,3000,2000,1,30.0,4000,480.0,4.0,3,33,4000,0,0,0,1,5,0,No
454
+ 0,700,700,0,30.0,7300,300.0,3.0,2,31,5000,0,0,1,0,1,0,Yes
455
+ 0,7000,5000,1,30.0,10000,1300.0,5.0,3,40,2000,0,0,1,1,4,0,No
456
+ 0,2000,2000,0,30.0,9000,3000.0,3.0,1,44,5000,0,1,1,1,5,1,Yes
457
+ 0,2000,2000,0,15.0,2500,300.0,21.0,2,54,4000,0,0,0,1,5,0,Yes
458
+ 0,700,500,1,24.0,1000,100.0,2.0,1,33,5000,0,0,1,0,1,0,No
459
+ 0,1500,1500,0,30.0,3000,375.0,4.0,1,22,1000,0,0,1,0,1,0,Yes
460
+ 1,2000,2000,0,30.0,1000,750.0,1.0,1,34,3000,1,0,0,0,1,0,Yes
461
+ 1,1500,1000,1,36.0,3000,240.0,3.0,2,37,1500,0,0,0,0,1,0,No
462
+ 1,2000,2000,0,60.0,50000,560.0,3.0,1,32,8500,0,0,0,0,1,0,Yes
463
+ 1,1500,1000,1,30.0,4500,500.0,3.0,1,30,1500,0,1,0,0,1,0,No
464
+ 1,8000,7000,1,60.0,5000,4000.0,2.0,3,33,8000,0,0,0,1,4,0,No
465
+ 0,4000,4000,0,36.0,50000,6000.0,3.0,1,49,7000,0,1,1,1,3,1,Yes
466
+ 0,4500,4000,1,30.0,5000,400.0,6.0,2,43,4500,0,0,0,1,3,0,No
467
+ 0,5000,5000,0,30.0,7000,3000.0,2.0,3,30,6000,1,0,0,0,4,0,Yes
468
+ 1,10000,7000,1,60.0,8000,250.0,2.0,2,39,6000,1,1,1,0,2,0,No
469
+ 1,2500,2500,0,60.0,3580,656.0,6.0,1,34,2000,1,1,1,0,1,0,Yes
470
+ 1,1500,1000,1,12.0,2200,237.0,4.0,1,56,1800,1,0,0,1,4,0,No
471
+ 1,700,700,0,12.0,1800,425.0,6.0,1,36,20000,0,0,1,1,4,0,Yes
472
+ 1,12000,7000,1,60.0,17440,204.0,3.0,1,35,8000,0,1,1,1,4,0,No
473
+ 0,3000,3000,0,60.0,5000,450.0,4.0,1,39,5000,0,0,1,1,2,0,Yes
474
+ 1,6000,6000,0,30.0,8700,2000.0,5.0,1,45,1600,0,0,0,0,1,0,Yes
475
+ 0,9000,9000,0,30.0,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,Yes
476
+ 1,5000,3000,1,30.0,6000,800.0,2.5,1,42,1000,0,0,1,0,1,0,No
477
+ 1,6000,6000,0,60.0,5000,600.0,5.0,1,30,1000,0,1,1,0,2,0,Yes
478
+ 1,900,800,1,60.0,4500,300.0,20.0,1,45,4500,1,1,1,0,1,0,No
479
+ 1,2500,2000,1,60.0,5000,530.0,7.0,1,45,2000,0,0,0,0,1,0,No
480
+ 0,700,500,1,60.0,3000,450.0,6.0,1,30,2500,0,0,0,1,5,0,No
481
+ 1,2000,2000,0,30.0,4150,828.0,2.0,1,37,3000,0,0,1,0,1,0,Yes
482
+ 1,2000,2000,0,30.0,3000,580.0,4.0,1,35,4000,0,0,1,0,1,0,Yes
483
+ 1,300,300,0,15.0,6000,450.0,3.0,1,32,2000,0,0,1,0,1,0,Yes
484
+ 1,6000,5000,1,45.0,10000,1100.0,9.0,1,38,5000,0,1,0,1,4,0,No
485
+ 1,600,600,0,15.0,1700,180.0,7.0,3,33,3700,0,0,0,1,4,0,Yes
486
+ 1,2000,1000,1,30.0,7000,700.0,2.0,1,36,4000,0,0,0,1,5,0,No
487
+ 1,7200,7200,1,60.0,9000,0.0,0.0,2,36,9000,1,0,1,0,1,0,Yes
488
+ 1,200,200,0,24.0,7000,450.0,5.0,1,30,10000,0,0,1,0,1,0,Yes
489
+ 0,1000,1000,0,30.0,5100,470.0,9.0,2,49,2000,1,0,1,1,4,0,Yes
490
+ 1,2000,2000,0,20.0,4000,600.0,5.0,1,26,2200,0,0,0,0,1,0,Yes
491
+ 0,9000,9000,0,30.0,12000,900.0,3.0,3,35,9000,1,0,0,1,4,1,Yes
492
+ 1,1000,1000,0,30.0,2500,800.0,3.0,2,30,2000,0,0,1,0,3,0,Yes
493
+ 0,9000,9000,0,60.0,1500,450.0,2.0,2,39,5000,0,0,0,0,3,0,Yes
494
+ 0,9000,8000,1,36.0,9000,700.0,3.0,3,55,9000,1,0,1,1,3,0,No
495
+ 0,5000,5000,0,30.0,8000,2000.0,7.0,1,37,1000,0,0,1,0,1,0,Yes
496
+ 1,500,500,0,60.0,5400,500.0,6.0,3,42,3200,0,0,1,1,4,0,Yes
497
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
498
+ 0,5000,3000,1,30.0,12000,1500.0,20.0,2,53,5000,0,0,1,0,3,0,No
499
+ 0,9000,6000,1,30.0,8000,800.0,2.0,4,33,8000,0,0,1,0,4,1,No
500
+ 0,6000,6000,0,30.0,10000,900.0,20.0,2,53,7000,0,0,1,0,3,0,Yes
501
+ 1,300,300,0,60.0,3200,400.0,2.0,1,27,1700,0,0,1,0,4,0,Yes
502
+ 1,1200,1200,0,36.0,7000,700.0,5.0,1,37,5000,1,0,0,1,5,0,Yes
503
+ 0,1000,1000,0,30.0,2500,500.0,18.0,1,45,6300,0,0,0,1,1,0,Yes
504
+ 0,3000,3000,0,30.0,17000,4300.0,4.0,1,43,9000,0,1,0,1,3,1,Yes
505
+ 1,1400,1400,0,60.0,7000,185.0,4.0,2,29,2000,0,0,1,0,1,0,Yes
506
+ 1,8000,8000,0,36.0,2800,300.0,11.0,2,49,9000,1,0,1,0,2,0,Yes
507
+ 1,8000,8000,0,60.0,4000,450.0,3.0,3,43,7000,0,0,1,0,3,0,Yes
508
+ 1,1000,1000,0,60.0,3000,500.0,3.0,1,50,3000,1,0,0,0,1,0,Yes
509
+ 0,9000,9000,0,,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,Yes
510
+ 0,3000,3000,0,30.0,6500,900.0,6.0,3,33,2000,0,0,0,1,5,0,Yes
511
+ 1,700,500,1,60.0,800,185.0,2.0,1,26,450,1,0,1,0,1,0,No
512
+ 0,7000,7000,0,60.0,20000,3000.0,4.0,1,53,8000,0,1,1,0,3,1,Yes
513
+ 0,35000,30000,1,36.0,15000,3000.0,10.0,1,35,15000,1,0,0,0,1,0,No
514
+ 1,4000,4000,0,30.0,3250,400.0,9.0,2,44,5000,0,1,0,1,4,0,Yes
515
+ 0,6000,5000,1,30.0,8000,250.0,6.0,2,43,7000,0,0,0,0,3,0,No
516
+ 1,9000,6000,1,60.0,9000,1200.0,8.0,3,40,7000,1,1,0,1,4,0,No
517
+ 1,3000,3000,0,30.0,4700,500.0,4.0,1,32,4000,1,0,0,1,1,0,Yes
518
+ 1,1000,1000,0,30.0,2000,800.0,2.0,1,50,2000,0,0,1,0,1,0,Yes
519
+ 1,600,600,0,30.0,1200,190.0,2.0,3,48,1000,0,0,1,1,4,0,Yes
520
+ 0,9000,6000,1,60.0,8000,800.0,2.0,4,33,8000,0,0,0,0,4,1,No
521
+ 1,2500,2500,0,60.0,10000,1200.0,8.0,1,39,3000,1,0,1,0,1,0,Yes
522
+ 1,1500,1100,1,30.0,3000,264.0,4.0,2,59,1200,0,0,0,0,1,0,No
523
+ 0,5000,3000,1,60.0,7000,1000.0,2.0,3,36,3000,1,0,0,1,4,0,No
524
+ 1,5000,5000,0,30.0,1000,180.0,10.0,4,40,5000,0,0,1,1,3,1,Yes
525
+ 1,1000,1000,0,30.0,1500,256.0,6.0,3,51,2000,1,0,1,1,4,0,Yes
526
+ 1,4000,4000,0,30.0,10000,1100.0,3.0,1,44,1000,1,0,0,0,1,0,Yes
527
+ 1,600,600,0,60.0,3900,400.0,5.0,2,32,2000,0,0,0,0,1,0,Yes
528
+ 1,200,200,0,60.0,5000,360.0,1.0,1,25,5000,0,1,0,0,1,0,Yes
529
+ 1,1000,1000,0,30.0,5000,600.0,6.0,3,60,6000,1,1,0,0,1,0,Yes
530
+ 1,500,500,0,60.0,3000,600.0,5.0,3,30,3000,1,1,1,1,1,0,Yes
531
+ 1,8000,8000,0,60.0,4000,450.0,3.0,3,43,7000,0,0,1,0,3,0,Yes
532
+ 1,5000,3000,1,30.0,5000,1400.0,1.0,1,40,4000,1,0,1,0,1,0,No
533
+ 0,500,500,0,36.0,3100,700.0,1.0,2,34,3000,0,0,0,0,1,0,Yes
534
+ 1,600,600,0,24.0,2000,300.0,5.0,1,26,10000,0,0,1,1,4,0,Yes
535
+ 1,8000,7000,1,60.0,10000,700.0,2.0,3,33,8000,1,0,0,1,4,0,No
536
+ 0,10000,7000,1,30.0,4000,400.0,8.0,4,60,9000,1,0,1,1,4,1,No
537
+ 1,15000,10000,1,30.0,3600,250.0,1.0,2,40,9000,0,1,0,0,5,0,No
538
+ 1,6000,6000,0,,9500,900.0,7.0,2,28,9000,1,1,1,1,3,0,Yes
539
+ 1,1200,1200,0,30.0,2400,288.0,2.0,1,29,1500,0,0,0,0,1,0,Yes
540
+ 1,4000,4000,0,30.0,9000,900.0,4.0,1,45,1200,0,0,1,0,1,0,Yes
541
+ 0,4000,4000,0,30.0,9000,867.0,5.0,1,27,4500,1,1,1,1,1,0,Yes
542
+ 0,5000,5000,0,30.0,12000,1500.0,8.0,1,40,1200,1,0,1,1,5,0,Yes
543
+ 1,3000,3000,0,30.0,2610,156.0,6.0,1,32,5200,0,0,0,0,1,0,Yes
544
+ 1,1400,1400,0,60.0,7000,320.0,3.0,2,29,2000,1,0,0,0,1,0,Yes
545
+ 0,1000,1000,0,20.0,2500,285.0,4.0,3,55,1510,1,0,1,1,4,0,Yes
546
+ 1,1000,1000,0,30.0,10000,400.0,3.0,1,33,3000,0,1,1,0,5,1,Yes
547
+ 0,50000,30000,1,36.0,10000,900.0,15.0,1,40,10000,0,0,0,0,2,0,No
548
+ 1,5000,5000,0,15.0,3500,570.0,2.0,2,30,2000,0,0,0,0,1,0,Yes
549
+ 1,10000,7000,1,60.0,9000,600.0,4.0,4,49,9000,1,1,0,1,4,0,No
550
+ 1,5000,5000,0,30.0,8000,2000.0,5.0,1,45,1500,0,0,0,0,1,0,Yes
551
+ 1,500,500,0,24.0,1000,345.0,5.0,1,27,10000,1,0,0,0,1,0,Yes
552
+ 1,2600,2600,1,30.0,15000,162.0,5.0,1,40,2000,1,0,1,1,1,0,Yes
553
+ 1,2000,2000,0,60.0,3000,780.0,2.0,3,38,3000,1,0,1,0,4,0,Yes
554
+ 0,3000,3000,0,36.0,6000,750.0,2.0,1,30,390,0,0,0,0,1,0,Yes
555
+ 1,300,300,0,30.0,2500,250.0,8.0,1,30,2000,1,0,1,0,1,0,Yes
556
+ 0,9000,9000,0,30.0,5000,320.0,9.0,4,38,9000,1,1,1,1,1,1,Yes
557
+ 0,3000,3000,0,40.0,3500,450.0,3.0,1,48,4000,0,0,0,0,5,0,Yes
558
+ 1,12000,10000,1,30.0,7000,6000.0,2.0,1,33,12000,0,1,0,0,4,0,No
559
+ 0,9000,9000,0,30.0,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,Yes
560
+ 1,2000,1000,1,60.0,4000,800.0,1.0,1,34,4000,1,0,1,1,5,0,No
561
+ 0,2000,2000,0,30.0,4200,834.0,7.0,1,32,3000,0,0,1,0,1,0,Yes
562
+ 0,9000,9000,0,30.0,5000,320.0,9.0,4,38,9000,1,1,1,1,1,1,Yes
563
+ 0,1000,1000,0,24.0,2500,285.0,4.0,3,55,1510,1,0,1,1,4,0,Yes
564
+ 0,8000,7000,1,36.0,5000,4000.0,2.0,3,39,9700,0,1,1,1,4,0,No
565
+ 0,5000,5000,0,30.0,8000,580.0,5.0,3,39,5000,0,0,1,0,4,0,Yes
566
+ 0,1000,1000,0,20.0,2000,250.0,2.0,1,28,2000,0,0,1,0,1,0,Yes
567
+ 0,2500,1500,0,60.0,5120,552.0,4.0,1,40,1500,1,0,1,1,1,0,No
568
+ 0,20000,20000,0,36.0,14000,7000.0,7.0,3,49,9000,0,1,1,1,3,1,Yes
569
+ 1,800,800,0,36.0,1600,192.0,4.0,1,43,5000,0,0,1,1,4,0,Yes
570
+ 1,800,600,1,30.0,12000,900.0,4.0,1,44,4500,0,0,0,1,4,0,No
571
+ 0,7000,7000,1,60.0,10000,359.0,12.0,3,39,8000,1,0,1,1,4,0,Yes
572
+ 1,2000,2000,0,36.0,5000,700.0,7.0,1,44,5000,1,0,0,1,4,0,Yes
573
+ 0,5000,3000,1,30.0,2000,1600.0,1.0,1,43,4000,0,0,1,0,1,0,No
574
+ 0,7000,5500,1,30.0,7000,400.0,5.0,2,45,5000,0,0,1,1,4,0,No
575
+ 0,1000,1000,0,30.0,7000,600.0,9.0,3,29,600,0,1,0,0,5,1,Yes
576
+ 0,500,500,0,36.0,2400,400.0,6.0,2,38,2000,1,0,0,0,1,0,Yes
577
+ 0,2500,2500,0,60.0,6000,650.0,3.0,1,35,3000,0,0,1,0,1,0,Yes
578
+ 0,1000,1000,0,30.0,3000,500.0,6.0,3,37,4500,0,0,0,1,5,0,Yes
579
+ 0,1500,1500,0,30.0,4460,885.0,12.0,1,26,1500,1,0,0,0,1,0,Yes
580
+ 0,9000,9000,0,30.0,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,Yes
581
+ 0,3000,3000,0,36.0,5000,500.0,4.0,1,32,7000,0,0,1,1,5,0,Yes
582
+ 1,544,544,0,20.0,1800,108.0,5.0,2,32,1000,0,0,0,0,1,0,Yes
583
+ 1,900,900,0,15.0,1500,450.0,5.0,1,32,4500,0,0,0,0,1,0,Yes
584
+ 1,5000,3000,1,36.0,4000,1500.0,5.0,1,42,4000,0,0,0,0,1,0,No
585
+ 1,3000,3000,0,12.0,8000,870.0,4.0,1,38,3000,1,1,0,0,1,0,Yes
586
+ 0,8000,5000,1,50.0,7000,450.0,4.0,1,49,1500,1,1,0,1,1,0,No
587
+ 1,500,500,0,30.0,1000,152.0,1.0,3,40,659,0,0,1,1,5,0,Yes
588
+ 1,5000,5000,0,30.0,8000,500.0,7.0,1,37,1500,0,0,1,0,1,0,Yes
589
+ 0,400,357,1,15.0,4000,450.0,4.0,1,50,5000,0,0,1,1,1,0,No
590
+ 1,2500,2500,0,30.0,0,0.0,0.0,3,30,5000,0,0,0,0,3,0,Yes
591
+ 0,600,600,0,30.0,600,180.0,3.0,3,50,1800,0,0,1,0,5,0,Yes
592
+ 1,7000,5000,1,60.0,900,190.0,1.0,2,43,4000,0,1,0,0,4,0,No
593
+ 1,900,750,1,60.0,3000,350.0,21.0,1,56,3000,1,1,1,0,4,0,No
594
+ 0,800,500,1,30.0,1500,500.0,4.0,1,36,1000,1,0,0,0,1,0,No
595
+ 0,1000,1000,0,25.0,6000,670.0,4.0,1,47,1200,0,1,1,0,1,0,Yes
596
+ 0,7500,7500,0,60.0,14000,165.0,5.0,3,45,10000,0,0,0,1,4,0,Yes
597
+ 1,10000,7000,1,60.0,9000,600.0,4.0,4,49,9000,1,1,0,1,4,0,No
598
+ 1,10000,8000,1,30.0,7000,540.0,1.5,3,30,9000,1,0,0,0,4,0,No
599
+ 1,10000,7000,1,60.0,9000,600.0,4.0,4,49,9000,1,1,0,1,4,0,No
600
+ 0,5000,5000,0,60.0,5000,550.0,4.0,3,45,6000,0,1,0,1,4,0,Yes
601
+ 1,2000,2000,0,30.0,2000,760.0,3.0,3,32,3000,0,0,1,1,4,0,Yes
602
+ 0,5000,5000,0,36.0,9000,800.0,2.0,1,32,1200,1,0,1,0,1,0,Yes
603
+ 1,2000,2000,0,40.0,1740,365.0,6.0,1,25,1500,0,1,1,1,1,0,Yes
604
+ 1,2000,2000,0,30.0,3600,400.0,3.0,2,35,3000,1,0,0,0,5,0,Yes
605
+ 1,5000,5000,0,60.0,12000,700.0,5.0,1,27,1200,1,0,1,0,2,0,Yes
606
+ 0,3000,3000,0,30.0,5000,200.0,4.0,1,38,2000,0,1,0,0,2,0,Yes
607
+ 1,800,800,0,24.0,1600,200.0,3.0,1,36,1000,0,0,1,0,1,0,Yes
608
+ 1,1500,1000,1,24.0,2000,400.0,4.0,2,32,1500,0,0,0,1,4,0,No
609
+ 1,1000,1000,0,36.0,6000,500.0,7.0,1,33,3000,0,0,0,0,1,0,Yes
610
+ 1,1000,1000,0,36.0,7000,600.0,3.0,1,37,3000,0,0,1,0,1,0,Yes
611
+ 0,800,300,1,15.0,6000,450.0,3.0,1,28,1600,0,1,0,0,5,1,No
612
+ 1,4000,4000,0,36.0,7000,700.0,7.0,1,42,6000,1,0,1,1,5,0,Yes
613
+ 1,600,600,0,30.0,4100,300.0,6.0,2,43,2000,0,0,0,0,1,0,Yes
614
+ 1,1000,1000,0,30.0,2500,562.0,5.0,1,28,10000,1,0,1,0,1,0,Yes
615
+ 1,3000,3000,0,30.0,4000,1100.0,17.0,1,44,4000,0,0,1,0,1,0,Yes
616
+ 1,8000,8000,0,60.0,600,100.0,5.0,1,30,9000,1,1,1,1,2,0,Yes
617
+ 1,5000,3000,0,60.0,9700,550.0,1.0,1,29,3000,1,0,0,1,1,0,No
618
+ 1,5000,4000,1,30.0,1000,180.0,10.0,4,40,5000,0,0,1,1,3,1,No
619
+ 1,500,500,0,60.0,2400,400.0,9.0,2,45,3400,0,0,1,0,1,0,Yes
620
+ 0,6000,6000,0,60.0,12000,600.0,20.0,2,53,5000,0,0,1,1,3,0,Yes
621
+ 0,6000,6000,0,30.0,70000,1800.0,3.0,1,49,12000,1,1,0,0,3,1,Yes
622
+ 0,12000,12000,0,60.0,30000,240.0,15.0,3,41,45000,1,0,1,1,4,0,Yes
623
+ 1,15000,8000,1,30.0,3600,250.9,5.0,2,30,9000,0,1,1,0,4,0,No
624
+ 0,500,500,0,15.0,1000,250.0,5.0,1,42,4000,0,0,1,1,2,0,Yes
625
+ 0,1000,1000,0,60.0,6000,500.0,7.0,1,33,3000,0,0,1,1,1,0,Yes
626
+ 1,5000,5000,0,30.0,8000,800.0,3.0,1,45,1400,1,0,0,1,5,0,Yes
627
+ 0,5000,5000,0,30.0,10000,800.0,7.0,1,37,1000,1,0,1,1,4,0,Yes
628
+ 1,1500,1000,1,30.0,3500,550.0,4.0,1,27,4000,0,0,1,1,4,0,No
629
+ 0,2500,2500,0,60.0,1800,500.0,5.0,3,39,7000,0,0,1,1,1,0,Yes
630
+ 0,5000,1600,1,30.0,5000,686.0,6.0,1,28,15000,1,0,1,0,4,0,No
631
+ 1,600,600,0,36.0,7000,400.0,8.0,1,40,2000,0,0,1,1,4,0,Yes
632
+ 1,500,500,0,30.0,1200,145.0,5.0,1,28,1500,0,0,1,1,1,0,Yes
633
+ 1,700,700,0,15.0,7000,200.0,4.0,3,29,1500,0,1,0,1,5,1,Yes
634
+ 1,8000,8000,0,30.0,4600,3000.0,2.0,2,29,1000,0,1,1,1,4,0,Yes
635
+ 0,500,400,1,60.0,1000,165.0,2.0,1,25,500,0,0,0,1,1,0,No
636
+ 1,300,300,0,15.0,3600,600.0,26.0,2,50,1800,0,0,0,0,1,0,Yes
637
+ 1,3000,1000,1,30.0,6000,400.0,5.0,3,32,4000,0,1,1,0,1,0,No
638
+ 0,1500,1200,1,20.0,2400,250.0,2.0,1,43,1500,0,0,1,1,4,0,No
639
+ 0,7000,5500,1,30.0,7000,400.0,5.0,2,45,5000,0,0,1,1,4,0,No
640
+ 0,10000,8000,1,30.0,2310,552.0,0.5,3,40,10000,1,0,0,1,4,0,No
641
+ 1,2000,2000,0,60.0,2000,620.0,3.0,2,33,2000,0,0,1,0,3,0,Yes
642
+ 0,8000,8000,0,60.0,10000,109.0,3.0,3,55,1510,0,0,1,1,4,0,Yes
643
+ 1,4000,4000,0,30.0,12430,1400.0,6.0,1,24,5000,1,0,1,1,1,0,Yes
644
+ 0,2000,1000,1,15.0,5000,600.0,4.0,2,30,600,0,1,1,1,5,0,No
645
+ 1,9000,6000,1,30.0,10000,5000.0,2.0,3,38,9500,1,1,1,0,4,0,No
646
+ 0,5000,5000,0,60.0,8000,600.0,2.0,1,28,8000,0,0,0,0,5,0,Yes
647
+ 1,1600,1600,0,25.0,7500,125.0,9.0,2,40,12000,0,0,1,0,3,0,Yes
648
+ 1,500,500,0,20.0,1000,200.0,3.0,3,34,1100,0,0,0,1,4,0,Yes
649
+ 0,9000,6000,1,30.0,8000,800.0,2.0,4,33,8000,0,0,1,0,4,1,No
650
+ 0,600,600,0,30.0,8000,600.0,3.0,3,28,6000,1,0,1,1,4,0,Yes
651
+ 1,15000,10000,1,60.0,5000,590.0,4.0,1,29,12000,0,0,1,0,1,0,No
652
+ 0,400,400,0,20.0,8000,960.0,4.0,1,48,1000,0,0,1,0,1,0,Yes
653
+ 1,5000,2000,1,60.0,6000,2000.0,2.0,1,40,4000,0,0,0,1,5,0,No
654
+ 0,3000,3000,0,15.0,6500,450.0,3.0,3,31,4000,1,0,0,1,5,0,Yes
655
+ 0,400,400,0,15.0,1500,450.0,4.0,2,29,4500,0,0,1,0,3,0,Yes
656
+ 1,700,700,0,36.0,1400,100.0,5.0,1,46,6000,0,0,1,0,1,0,Yes
657
+ 1,2000,2000,0,30.0,2000,650.0,2.0,3,38,3000,1,0,1,1,4,0,Yes
658
+ 0,800,400,1,60.0,800,185.0,6.0,1,49,3000,1,0,0,0,1,0,No
659
+ 0,6000,5000,0,30.0,9000,700.0,4.0,1,28,5000,1,0,0,1,1,0,No
660
+ 0,7000,7000,0,60.0,8000,750.0,3.0,1,30,750,1,1,0,0,2,0,Yes
661
+ 1,10000,8000,1,30.0,2310,552.0,0.5,3,40,8000,1,0,0,1,4,0,No
662
+ 1,2000,2000,0,60.0,2000,700.0,3.0,3,35,3000,0,0,0,1,4,0,Yes
663
+ 1,2000,1500,0,30.0,9000,1000.0,1.0,3,25,4000,0,0,1,1,4,0,No
664
+ 0,20000,12000,1,36.0,45000,16000.0,4.0,1,42,9000,0,1,1,0,1,1,No
665
+ 0,5000,5000,0,36.0,9000,600.0,3.0,1,36,1300,1,0,0,1,4,0,Yes
666
+ 0,1000,1000,0,30.0,3000,327.0,14.0,1,35,1500,0,1,1,0,1,0,Yes
667
+ 1,1500,1500,0,20.0,3000,360.0,3.0,1,29,6000,0,0,1,0,1,0,Yes
668
+ 1,2000,2000,0,30.0,3500,1000.0,4.0,1,35,4000,0,0,0,0,4,0,Yes
669
+ 1,1000,1000,0,30.0,1000,120.0,3.0,3,28,1800,0,0,1,1,5,0,Yes
670
+ 1,5000,5000,0,30.0,1000,180.0,10.0,4,40,7000,0,0,1,1,3,1,Yes
671
+ 0,9000,9000,0,60.0,15000,369.0,5.0,1,63,30000,1,0,0,0,2,0,Yes
672
+ 1,2000,2000,0,30.0,6200,900.0,2.0,2,38,1400,0,0,0,1,1,0,Yes
673
+ 0,2000,1500,1,60.0,2660,432.0,5.0,1,57,2000,0,0,1,1,1,0,No
674
+ 1,400,400,0,30.0,8000,700.0,2.0,1,20,1500,1,0,1,1,4,0,Yes
675
+ 0,1000,1000,0,30.0,1500,164.0,6.0,1,33,6000,1,0,0,0,1,0,Yes
676
+ 1,2000,1500,1,30.0,2400,570.0,3.0,1,26,2000,1,0,0,1,4,0,No
677
+ 0,1600,1600,0,60.0,5000,285.0,3.0,3,48,4000,1,0,0,1,4,0,Yes
678
+ 1,600,550,1,60.0,3000,450.0,25.0,1,50,3000,1,1,1,0,4,0,No
679
+ 1,10000,7000,1,60.0,8000,250.0,2.0,2,39,6000,1,1,1,0,2,0,No
680
+ 0,2000,2000,0,30.0,2500,255.0,8.0,1,43,6000,1,0,0,0,1,0,Yes
681
+ 0,10000,8000,1,36.0,3000,2500.0,1.0,3,25,3000,1,0,0,0,4,0,No
682
+ 0,10000,10000,0,60.0,25000,15000.0,6.0,1,43,12000,1,1,1,1,3,1,Yes
683
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
684
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
685
+ 1,2000,2000,0,60.0,3100,545.0,15.0,1,38,1500,1,1,1,1,1,0,Yes
686
+ 0,5000,5000,0,30.0,12000,750.0,20.0,2,53,7000,0,0,0,0,3,0,Yes
687
+ 0,500,500,0,36.0,1000,200.0,1.0,1,32,2000,1,0,0,0,1,0,Yes
688
+ 1,7000,7000,0,30.0,15000,8000.0,6.0,1,47,8000,0,1,1,0,3,1,Yes
689
+ 1,3000,3000,0,30.0,6000,720.0,4.0,3,54,2000,0,0,1,0,1,0,Yes
690
+ 1,700,500,1,20.0,1000,100.0,2.0,1,25,1000,0,0,0,1,4,0,No
691
+ 0,10000,7000,1,60.0,17440,5000.0,3.0,1,35,10000,0,1,1,1,4,0,No
692
+ 1,5000,5000,0,15.0,4500,700.0,5.0,2,35,2000,1,0,1,1,4,0,Yes
693
+ 1,500,500,0,36.0,1000,120.0,2.0,1,39,950,0,0,0,1,4,0,Yes
694
+ 1,4000,4000,0,60.0,14000,7000.0,4.0,1,43,6000,1,1,1,0,1,1,Yes
695
+ 0,800,800,0,30.0,1500,400.0,5.0,2,38,4500,0,0,1,1,3,0,Yes
696
+ 1,2000,2000,0,30.0,7000,500.0,7.0,1,44,5000,0,0,0,0,1,0,Yes
697
+ 1,2000,1800,1,30.0,6000,350.0,15.0,3,54,1500,1,1,1,1,5,1,No
698
+ 1,2000,2000,0,30.0,1000,760.0,2.0,2,34,1000,0,0,0,0,3,0,Yes
699
+ 0,10000,10000,0,50.0,14000,925.0,2.0,1,49,12000,0,0,1,0,1,0,Yes
700
+ 1,5000,2000,1,12.0,2000,1500.0,4.0,1,41,4000,0,0,1,0,5,0,No
701
+ 1,10000,10000,0,60.0,14000,5000.0,5.0,3,43,9000,0,1,1,0,3,1,Yes
702
+ 1,400,400,0,15.0,1000,200.0,8.0,1,28,5000,0,0,0,1,5,0,Yes
703
+ 0,10000,7000,1,30.0,4000,400.0,8.0,4,60,7000,1,0,1,1,4,1,No
704
+ 0,5000,4000,1,15.0,8000,600.0,5.0,2,41,7000,0,0,1,0,3,0,No
705
+ 1,2000,2000,0,30.0,2500,770.0,2.0,1,34,3000,0,0,0,0,1,0,Yes
706
+ 1,5000,2000,1,12.0,5000,800.0,1.5,3,50,3000,1,0,1,1,4,0,No
707
+ 1,2000,2000,0,60.0,2000,720.0,1.0,1,36,3000,0,0,1,0,1,0,Yes
708
+ 0,3000,3000,1,60.0,4655,479.0,8.0,1,37,5000,0,0,0,1,1,0,Yes
709
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
710
+ 0,10000,7000,1,30.0,4000,400.0,8.0,4,60,9000,0,0,1,1,4,1,No
711
+ 0,700,500,1,60.0,3000,450.0,6.0,1,30,2500,0,0,0,1,5,0,No
712
+ 0,2000,2000,0,60.0,5600,650.0,12.0,1,52,5000,1,0,1,0,1,0,Yes
713
+ 1,500,500,0,30.0,7000,400.0,7.0,1,47,1000,0,0,1,0,1,0,Yes
714
+ 0,50000,50000,0,36.0,20000,3000.0,25.0,1,50,20000,1,0,1,0,4,0,Yes
715
+ 0,4500,4500,0,60.0,42000,6900.0,2.0,1,47,7000,1,1,0,1,1,1,Yes
716
+ 1,5000,5000,0,60.0,1000,500.0,3.0,3,32,5000,1,1,1,0,4,0,Yes
717
+ 0,3000,1000,1,36.0,3000,750.0,4.0,1,36,2000,1,0,1,0,1,0,No
718
+ 0,2000,2000,0,36.0,50000,1600.0,2.0,1,25,4500,1,1,1,1,3,1,Yes
719
+ 1,8000,8000,0,30.0,4600,3000.0,2.0,2,29,10000,0,0,1,1,4,0,Yes
720
+ 0,15000,3500,1,30.0,6800,1000.0,4.0,2,29,1000,0,1,1,0,3,0,No
721
+ 1,10000,8000,1,60.0,18000,4500.0,4.0,1,42,9000,0,1,0,1,5,1,No
722
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
723
+ 0,1000,1000,0,30.0,4900,400.0,7.0,1,36,1500,0,0,1,0,1,0,Yes
724
+ 1,1600,1600,0,25.0,12000,125.0,9.0,2,40,12000,1,0,1,0,3,0,Yes
725
+ 1,600,500,1,60.0,12000,1000.0,4.0,1,29,7000,0,1,1,0,1,0,No
726
+ 0,9000,9000,0,30.0,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,Yes
727
+ 1,600,600,0,15.0,1000,300.0,15.0,1,50,4000,0,0,0,1,5,0,Yes
728
+ 1,7000,5000,1,60.0,1800,300.0,0.0,1,40,4000,1,0,1,0,3,0,No
729
+ 1,9000,6000,1,60.0,9000,1200.0,8.0,3,40,7000,1,1,0,1,4,0,No
730
+ 1,5000,5000,0,30.0,1000,180.0,10.0,4,40,7000,0,0,1,1,3,1,Yes
731
+ 0,9000,9000,0,30.0,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,Yes
732
+ 1,2000,1500,1,30.0,3000,300.0,2.0,2,35,1200,1,0,0,0,1,0,No
733
+ 0,1200,1000,1,30.0,5000,746.0,10.0,3,32,2000,1,1,1,1,5,0,No
734
+ 1,5000,2000,1,60.0,8000,1200.0,1.0,3,38,2000,0,0,1,1,4,0,No
735
+ 1,5000,5000,0,36.0,12000,1250.0,7.0,1,45,6000,0,1,1,1,4,0,Yes
736
+ 0,1000,1000,0,30.0,8000,2000.0,1.0,1,27,3000,0,1,1,1,5,1,Yes
737
+ 1,1000,1000,0,30.0,3000,535.0,5.0,1,33,15000,1,0,1,0,1,0,Yes
738
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
739
+ 0,5000,5000,0,60.0,15000,1800.0,3.0,1,47,8000,0,1,0,1,3,1,Yes
740
+ 1,2500,2500,0,60.0,6500,660.0,5.0,3,58,3000,1,0,0,1,4,0,Yes
741
+ 1,5000,5000,0,30.0,11000,1000.0,3.0,1,44,1300,0,0,1,1,5,0,Yes
742
+ 1,15000,15000,0,60.0,35000,565.0,4.0,3,33,12000,0,0,1,1,5,0,Yes
743
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
744
+ 1,2500,2500,0,30.0,7000,680.0,8.0,1,40,3000,1,0,0,1,4,0,Yes
745
+ 0,5000,5000,0,30.0,5300,600.0,3.0,1,42,6000,0,0,0,0,1,0,Yes
746
+ 1,5000,5000,0,30.0,3000,350.0,16.0,3,62,6000,0,0,0,0,4,0,Yes
747
+ 1,500,500,0,60.0,1100,200.0,2.0,2,28,3000,0,0,0,0,1,0,Yes
748
+ 0,2000,1500,1,30.0,22000,1100.0,6.0,1,40,22000,0,0,0,0,5,0,No
749
+ 0,1500,1500,0,30.0,2500,225.0,8.0,1,46,2000,0,0,1,0,5,0,Yes
750
+ 0,1500,1500,0,20.0,3000,360.0,4.0,1,53,1000,0,0,1,0,1,0,Yes
751
+ 0,800,800,0,15.0,1500,280.0,4.0,1,28,5000,0,0,0,0,1,0,Yes
752
+ 1,5000,5000,0,30.0,3000,350.0,16.0,3,62,6000,0,0,0,0,4,0,Yes
753
+ 1,1500,1500,0,30.0,6700,700.0,5.0,2,46,3000,0,0,1,0,5,0,Yes
754
+ 0,2000,2000,0,30.0,3680,715.0,7.0,1,35,1500,1,1,0,0,1,0,Yes
755
+ 1,8000,8000,0,12.0,2800,300.0,4.5,2,49,9000,1,0,1,0,2,0,Yes
756
+ 1,1000,800,1,30.0,1600,240.0,2.0,3,27,8000,0,0,0,1,4,0,No
757
+ 0,1000,800,1,12.0,800,190.0,4.0,1,54,1000,1,0,1,0,1,0,No
758
+ 1,2000,2000,0,30.0,2500,902.0,2.0,1,38,3000,0,0,1,0,1,0,Yes
759
+ 1,2500,2500,0,60.0,1800,170.0,5.0,3,39,7000,0,0,0,0,1,0,Yes
760
+ 0,2000,2000,0,30.0,5000,700.0,7.0,1,36,5000,1,0,1,1,3,0,Yes
761
+ 0,1000,1000,1,36.0,6000,900.0,3.0,1,47,900,0,1,1,0,2,1,Yes
762
+ 0,15000,900,1,24.0,2000,450.0,11.0,1,30,20000,0,0,1,0,1,0,No
763
+ 0,2000,2000,0,30.0,35000,300.0,4.0,1,20,35000,0,0,0,0,1,0,Yes
764
+ 0,7000,5500,1,30.0,7000,400.0,5.0,2,45,5000,0,0,0,1,4,0,No
765
+ 0,4000,3000,1,60.0,6200,1080.0,8.0,1,43,1500,1,0,1,0,1,0,No
766
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
767
+ 1,6000,6000,0,30.0,20000,4900.0,6.0,1,41,11000,0,1,1,1,3,1,Yes
768
+ 1,4000,4000,0,30.0,3250,400.0,9.0,2,44,5000,0,1,1,1,4,0,Yes
769
+ 1,5000,5000,0,30.0,8000,800.0,6.0,1,27,1300,0,0,1,0,1,0,Yes
770
+ 0,600,600,0,36.0,1200,144.0,2.0,1,39,1200,0,0,0,0,1,0,Yes
771
+ 1,12000,7000,1,,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
772
+ 0,1500,1500,0,15.0,3000,225.0,5.0,1,38,4000,0,0,1,1,5,0,Yes
773
+ 0,2000,2000,0,30.0,4000,400.0,4.0,2,42,1100,1,0,1,1,4,0,Yes
774
+ 1,3000,3000,0,30.0,5000,560.0,6.0,1,40,4000,0,0,0,0,1,0,Yes
775
+ 0,12000,9000,1,30.0,3000,320.0,9.0,4,38,10000,1,1,1,1,1,1,No
776
+ 0,10000,8000,1,60.0,1000,130.0,3.0,3,32,9000,0,1,1,1,1,0,No
777
+ 1,6000,6000,0,30.0,3600,460.0,2.0,2,36,1000,0,0,0,0,4,0,Yes
778
+ 0,2000,2000,0,60.0,9000,150.0,2.0,2,50,5000,1,0,0,0,3,0,Yes
779
+ 1,500,500,0,60.0,2200,400.0,5.0,3,45,4000,1,0,1,1,5,0,Yes
780
+ 0,10000,9000,1,36.0,24000,12000.0,5.0,3,44,8000,0,1,0,1,3,1,No
781
+ 0,7000,5500,1,30.0,7000,400.0,5.0,2,45,5000,0,0,1,1,4,0,No
782
+ 1,2500,2000,1,30.0,3500,300.0,3.0,1,32,4000,0,0,0,0,1,0,No
783
+ 1,7000,7000,0,60.0,4000,500.0,3.0,1,35,9000,0,1,1,1,4,0,Yes
784
+ 1,500,500,0,15.0,1000,750.0,3.0,1,42,5000,0,0,0,0,1,0,Yes
785
+ 0,1600,1600,0,60.0,4500,150.0,3.0,2,35,4000,1,0,1,0,3,0,Yes
786
+ 0,5000,5000,0,30.0,1000,3000.0,5.0,3,35,7000,0,1,1,0,2,0,Yes
787
+ 1,1500,1400,1,30.0,40000,2400.0,4.0,1,47,6000,1,1,1,0,5,1,No
788
+ 1,3000,2800,1,30.0,12000,2400.0,3.0,1,29,7000,0,1,1,0,1,1,No
789
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
790
+ 0,1500,1500,0,30.0,2500,260.0,9.0,1,35,3000,0,0,1,0,1,0,Yes
791
+ 0,15000,15000,0,60.0,60000,4000.0,3.0,1,50,9000,1,1,0,0,3,1,Yes
792
+ 0,3000,1000,1,30.0,5000,250.0,2.0,1,28,2503,0,1,1,0,3,0,No
793
+ 0,600,600,0,60.0,1000,195.0,7.0,3,49,2500,1,0,1,1,5,0,Yes
794
+ 0,3500,3500,0,60.0,5000,350.0,4.0,3,33,7000,1,0,1,1,4,0,Yes
795
+ 0,8000,8000,0,30.0,8000,590.0,5.0,1,20,1500,0,0,1,0,1,0,Yes
796
+ 0,600,600,0,20.0,1200,150.0,2.0,1,42,7000,0,0,1,0,1,0,Yes
797
+ 1,10000,7000,1,60.0,8000,250.0,2.0,2,39,6000,1,1,1,0,2,0,No
798
+ 1,4000,3500,1,25.0,7500,251.0,3.0,1,43,11000,0,0,1,0,1,0,No
799
+ 1,300,300,0,15.0,1000,150.0,4.0,2,32,4000,0,0,0,1,5,0,Yes
800
+ 0,2000,1500,1,30.0,1500,954.0,6.0,1,39,1500,1,0,1,0,1,0,No
801
+ 1,10000,7000,1,60.0,9000,600.0,4.0,4,49,9000,1,1,0,1,4,0,No
802
+ 0,600,600,0,36.0,1200,180.0,3.0,1,49,1000,0,0,1,1,4,0,Yes
803
+ 0,2200,2200,0,60.0,6000,650.0,4.0,3,45,4000,0,0,1,1,4,0,Yes
804
+ 1,8000,8000,0,60.0,4000,450.0,3.0,3,43,7000,0,0,1,0,3,0,Yes
805
+ 0,10000,7000,1,30.0,4000,400.0,8.0,4,60,9000,1,0,1,1,4,1,No
806
+ 1,2000,2000,0,30.0,2500,690.0,1.0,1,42,3000,0,0,0,0,1,0,Yes
807
+ 0,9000,8000,1,120.0,9000,700.0,3.0,3,55,9000,1,0,1,1,3,0,No
808
+ 0,9000,8000,1,36.0,9000,700.0,3.0,3,55,9000,1,0,1,1,3,0,No
809
+ 1,1000,1000,0,30.0,1500,256.0,6.0,3,51,2000,1,0,0,1,4,0,Yes
810
+ 1,1500,1000,1,36.0,2000,100.0,1.0,3,58,1000,0,0,0,0,1,0,No
811
+ 1,1500,1500,0,30.0,2500,254.0,7.0,1,36,2000,0,0,0,0,1,0,Yes
812
+ 0,1500,1500,0,36.0,4600,900.0,11.0,1,36,20000,0,0,0,0,1,0,Yes
813
+ 1,1500,1500,0,30.0,2000,220.0,4.0,1,43,6000,1,0,0,0,1,0,Yes
814
+ 1,500,500,0,30.0,7000,1200.0,4.0,1,29,2000,0,0,1,1,4,0,Yes
815
+ 1,1000,1000,0,30.0,2100,400.0,7.0,2,44,5100,0,0,1,1,1,0,Yes
816
+ 1,3000,3000,0,30.0,4050,404.0,5.0,1,38,1500,0,0,1,0,1,0,Yes
817
+ 0,10000,8000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,No
818
+ 0,2500,2500,0,30.0,5000,375.0,2.0,3,35,500,0,0,1,1,4,0,Yes
819
+ 0,3500,3500,0,60.0,5000,350.0,4.0,3,33,7000,1,0,1,1,4,0,Yes
820
+ 1,2000,2000,0,60.0,2000,650.0,2.0,3,36,2000,0,0,1,1,4,0,Yes
821
+ 0,10000,8000,1,30.0,2310,6000.0,5.0,3,40,10000,1,0,1,1,4,0,No
822
+ 0,8000,8000,0,60.0,45000,2500.0,4.0,1,44,8000,0,1,1,0,3,1,Yes
823
+ 1,5000,1000,1,30.0,7000,820.0,2.0,3,44,2000,1,0,0,1,4,0,No
824
+ 0,600,600,0,30.0,4200,500.0,15.0,2,50,3000,0,0,0,0,1,0,Yes
825
+ 1,2000,2000,0,30.0,3500,370.0,5.0,1,41,1000,0,0,0,0,1,0,Yes
826
+ 0,2000,1500,1,30.0,3000,573.0,6.0,1,37,1500,1,0,0,0,1,0,No
827
+ 1,3000,3000,0,30.0,10000,1800.0,2.0,3,32,6000,0,1,0,0,1,1,Yes
828
+ 0,300,300,0,30.0,2270,262.0,1.0,1,34,800,0,0,0,1,1,0,Yes
829
+ 0,4000,3500,1,25.0,7500,450.0,3.0,2,51,4000,0,0,1,0,3,0,No
830
+ 0,30000,20000,1,60.0,40000,565.0,4.0,1,40,25000,1,0,1,0,2,0,No
831
+ 1,400,400,0,20.0,8000,100.0,3.0,1,27,1500,0,0,1,0,1,0,Yes
832
+ 1,2000,2000,0,30.0,3000,810.0,1.0,2,43,4000,1,0,1,1,3,0,Yes
833
+ 1,500,500,0,20.0,7000,200.0,2.0,1,41,600,0,1,0,1,4,0,Yes
834
+ 1,1000,1000,0,36.0,4700,600.0,25.0,2,52,7000,1,0,0,1,4,0,Yes
835
+ 1,200,200,0,15.0,1000,420.0,2.0,3,26,5000,0,0,1,1,5,0,Yes
836
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
837
+ 0,13000,3000,1,30.0,4000,200.0,3.0,3,30,5000,1,0,1,1,5,0,No
838
+ 0,2000,2000,0,36.0,1000,500.0,15.0,1,40,1000,0,0,0,0,1,0,Yes
839
+ 0,10000,8000,1,30.0,20000,400.0,20.0,2,52,20000,0,0,1,1,3,0,No
840
+ 1,12000,7000,1,60.0,17440,204.0,3.0,1,35,9000,0,1,1,1,4,0,No
841
+ 1,5000,5000,0,60.0,17000,1100.0,8.0,1,34,1500,0,0,1,1,4,0,Yes
842
+ 0,12000,10000,1,60.0,9000,400.0,5.0,3,39,7000,0,0,0,0,1,0,No
843
+ 1,500,500,0,60.0,1000,154.0,7.0,3,26,1000,1,0,1,1,4,0,Yes
844
+ 0,6000,6000,0,36.0,20000,3200.0,2.0,1,35,9000,0,1,0,1,3,1,Yes
845
+ 0,500,500,0,15.0,1200,700.0,4.0,1,29,1000,0,1,1,1,5,1,Yes
846
+ 1,300,300,0,30.0,3100,400.0,22.0,2,52,1400,0,0,0,0,1,0,Yes
847
+ 1,6000,6000,0,60.0,9500,900.0,7.0,2,28,9000,1,1,1,1,3,0,Yes
848
+ 0,1000,1000,0,30.0,4500,390.0,4.0,1,45,8000,0,0,1,0,1,0,Yes
849
+ 1,4000,4000,0,30.0,3250,400.0,9.0,2,44,5000,0,1,1,1,4,0,Yes
850
+ 1,1000,1000,0,30.0,9500,1000.0,5.0,3,38,1000,0,1,1,0,3,0,Yes
851
+ 0,5000,5000,0,15.0,1000,3000.0,5.0,3,35,7000,0,1,1,0,2,0,Yes
852
+ 0,9000,6000,1,30.0,8000,800.0,2.0,4,33,8000,0,0,0,0,4,1,No
853
+ 1,2000,2000,0,30.0,9000,700.0,7.0,1,45,5000,0,0,0,0,1,0,Yes
854
+ 1,4000,4000,0,30.0,3250,400.0,9.0,2,44,5000,0,1,1,1,4,0,Yes
855
+ 1,5000,5000,0,30.0,3000,350.0,16.0,3,62,6000,0,0,0,0,4,0,Yes
856
+ 0,9000,9000,0,30.0,5000,320.0,9.0,4,38,9000,1,1,1,1,1,1,Yes
857
+ 1,5000,4000,1,30.0,3000,350.0,16.0,3,62,6000,0,0,0,0,4,0,No
858
+ 0,1000,1000,0,60.0,35000,840.0,2.0,1,28,2000,0,1,1,1,5,1,Yes
859
+ 1,1000,1000,0,36.0,6000,400.0,7.0,1,37,3000,0,0,0,1,5,0,Yes
860
+ 1,3000,2000,1,30.0,2000,200.0,3.0,2,38,6000,0,0,0,0,3,0,No
861
+ 1,20000,12000,1,30.0,4000,200.0,3.0,3,30,8000,1,0,1,1,2,0,No
862
+ 1,500,500,0,30.0,1000,125.0,3.0,1,31,1000,1,0,1,1,4,0,Yes
863
+ 1,5000,4000,1,30.0,3250,400.0,9.0,2,44,5000,0,1,1,1,4,0,No
864
+ 1,5000,4000,1,36.0,1000,365.0,4.0,1,26,20000,0,0,1,1,4,0,No
865
+ 1,1500,1500,0,30.0,2900,300.0,6.0,2,29,4000,1,0,1,1,4,0,Yes
866
+ 0,7000,5000,1,30.0,9000,400.0,5.0,2,45,5000,0,0,1,1,4,0,No
867
+ 1,5000,5000,0,60.0,1000,180.0,1.0,1,42,4500,0,0,1,0,3,0,Yes
868
+ 0,5000,5000,0,30.0,9000,900.0,6.0,1,34,1300,0,0,1,1,5,0,Yes
869
+ 1,3000,3000,0,30.0,8000,300.0,9.0,1,36,1500,1,0,0,0,1,0,Yes
870
+ 1,7000,5000,1,60.0,5000,650.0,3.0,3,47,6000,1,1,1,0,4,0,No
871
+ 1,6000,6000,0,60.0,5800,600.0,28.0,2,50,3000,0,0,0,0,1,0,Yes
872
+ 0,12000,10000,1,30.0,60000,4000.0,2.0,1,52,9000,0,1,1,0,3,1,No
873
+ 1,1500,1500,0,30.0,3600,730.0,5.0,1,26,15000,0,0,1,0,1,0,Yes
874
+ 1,1000,1000,0,30.0,4000,1000.0,8.0,1,28,2000,0,0,1,0,1,0,Yes
875
+ 0,5000,5000,0,,4000,200.0,3.0,3,30,5000,1,0,1,1,5,0,Yes
876
+ 1,1500,1500,0,30.0,7000,1700.0,3.5,1,34,1700,0,1,0,0,1,0,Yes
877
+ 0,7000,5500,1,30.0,7000,400.0,5.0,2,45,5000,0,0,1,1,4,0,No
878
+ 0,2500,2000,1,30.0,2000,220.0,3.0,1,35,4000,0,1,0,0,1,0,No
879
+ 0,5000,4000,1,30.0,6000,400.0,20.0,2,52,5000,0,0,1,1,3,0,No
880
+ 1,5000,4500,1,60.0,4000,300.0,1.0,1,42,4500,1,0,0,1,3,0,No
881
+ 0,2000,1000,1,30.0,2250,537.0,1.0,1,27,1500,1,0,0,1,1,0,No
882
+ 0,5000,4000,1,30.0,8000,1800.0,4.0,3,35,2000,0,0,1,1,4,0,No
883
+ 1,5000,5000,0,30.0,1000,180.0,10.0,4,40,7000,0,0,1,1,3,1,Yes
884
+ 1,2500,2500,0,60.0,5000,0.0,0.0,3,30,5000,0,0,0,0,3,0,Yes
885
+ 1,800,800,0,30.0,2300,135.0,3.0,1,24,1500,0,0,1,1,1,0,Yes
886
+ 0,700,700,0,30.0,1500,300.0,7.0,3,37,4000,1,0,1,1,4,0,Yes
887
+ 1,300,300,0,12.0,5500,300.0,2.0,2,30,10000,0,0,1,0,1,0,Yes
888
+ 1,2000,2000,0,60.0,2500,590.0,2.0,2,34,2000,0,0,1,0,3,0,Yes
889
+ 1,1000,1000,0,20.0,2000,230.0,1.0,1,22,3000,1,0,1,1,4,0,Yes
890
+ 1,12000,7000,1,60.0,1800,200.0,7.0,2,42,8000,0,1,1,1,2,0,No
891
+ 1,1700,1500,1,60.0,12000,17000.0,6.0,3,49,7000,0,1,0,1,5,1,No
892
+ 0,9000,9000,0,30.0,5000,320.0,9.0,4,38,9000,1,1,1,1,1,1,Yes
893
+ 1,10000,10000,0,60.0,14000,8000.0,5.0,1,53,8000,0,1,0,0,3,1,Yes
894
+ 0,1500,1300,1,20.0,3000,300.0,2.0,1,40,7000,0,0,0,0,1,0,No
895
+ 1,2000,1000,1,30.0,3500,565.0,3.0,1,36,4000,0,0,0,1,4,0,No
896
+ 1,9000,5000,1,60.0,2000,250.0,2.0,2,39,6000,1,1,1,0,2,0,No
897
+ 1,1500,1000,1,30.0,2000,600.0,5.0,1,42,8000,0,0,0,0,1,0,No
898
+ 0,5000,5000,0,60.0,7500,600.0,0.0,1,45,10000,0,0,0,0,1,0,Yes
899
+ 0,5000,5000,0,30.0,12000,950.0,3.0,1,37,1300,1,0,0,1,5,0,Yes
900
+ 1,3000,3000,0,30.0,4000,170.0,5.0,1,28,7000,0,1,1,0,1,0,Yes
901
+ 0,5000,1500,1,30.0,4000,722.0,6.0,1,25,15000,0,0,0,0,1,0,No
902
+ 1,3000,3000,0,60.0,6000,0.0,0.0,1,46,7000,0,0,1,0,1,0,Yes
903
+ 1,1000,600,1,30.0,1200,252.0,2.0,1,25,2000,0,0,0,0,1,0,No
904
+ 0,7000,7000,0,60.0,15000,459.0,5.0,2,49,13000,0,0,0,1,5,0,Yes
905
+ 0,10000,8000,1,60.0,9000,2800.0,8.0,1,53,2800,0,1,1,0,2,0,No
906
+ 1,5000,5000,0,30.0,9000,1100.0,2.0,1,27,1000,0,0,1,1,5,0,Yes
907
+ 0,7000,5500,1,30.0,7000,400.0,5.0,2,45,5000,0,0,1,1,4,0,No
908
+ 1,1000,1000,0,30.0,3000,500.0,4.0,2,46,5000,0,0,0,0,1,0,Yes
909
+ 1,5000,5000,0,30.0,3000,350.0,16.0,3,62,6000,0,0,0,0,4,0,Yes
910
+ 1,9000,6000,1,30.0,9200,800.0,8.0,3,40,7000,1,1,0,1,4,0,No
911
+ 1,6000,5000,1,60.0,2000,250.0,1.0,1,42,5500,1,1,1,0,3,0,No
912
+ 1,1000,1000,0,30.0,2900,300.0,6.0,2,39,7000,0,0,1,1,4,0,Yes
913
+ 0,1500,1300,1,36.0,3000,325.0,2.0,1,49,800,0,0,1,0,1,0,No
914
+ 1,7000,5000,1,60.0,900,190.0,1.0,2,43,4000,0,1,0,0,4,0,No
915
+ 1,1600,1600,0,60.0,5000,443.0,8.0,3,35,2000,0,1,1,1,5,0,Yes
916
+ 1,5000,5000,0,30.0,9000,1000.0,9.0,1,24,1000,0,0,0,1,5,0,Yes
917
+ 1,4000,2000,1,12.0,4000,1500.0,4.0,1,41,3000,1,0,1,0,1,0,No
918
+ 0,10000,7000,1,30.0,4000,400.0,8.0,4,60,9000,1,0,1,1,4,1,No
919
+ 1,500,500,0,30.0,7000,400.0,5.0,1,47,1000,0,0,1,1,4,0,Yes
920
+ 1,8000,8000,0,36.0,2800,300.0,11.0,2,49,9000,1,0,1,0,2,0,Yes
921
+ 0,100000,80000,1,36.0,40000,4000.0,10.0,2,35,40000,1,0,0,0,4,0,No
922
+ 0,1500,1500,0,30.0,4000,809.0,3.0,3,38,2000,0,0,0,1,5,0,Yes
923
+ 1,800,500,1,30.0,4000,400.0,10.0,1,54,4000,0,0,0,0,1,0,No
924
+ 1,500,400,1,30.0,8000,900.0,2.0,1,31,9500,0,0,0,0,1,0,No
925
+ 0,400,400,0,30.0,3500,200.0,3.0,2,35,3500,0,0,1,0,1,0,Yes
926
+ 1,2000,2000,0,60.0,2500,600.0,1.0,3,35,4000,0,0,0,1,4,0,Yes
927
+ 1,2000,2000,0,60.0,10000,1002.0,7.0,1,34,4000,0,0,1,1,4,0,Yes
928
+ 1,1000,1000,1,30.0,15000,285.0,3.0,3,55,2500,0,0,0,1,4,0,Yes
929
+ 1,5000,5000,0,30.0,3000,350.0,16.0,3,62,6000,0,0,0,0,4,0,Yes
930
+ 0,10000,10000,0,60.0,15000,860.0,4.0,3,30,6000,1,0,1,1,4,0,Yes
931
+ 1,8000,8000,0,,4000,450.0,3.0,3,43,7000,0,0,1,0,3,0,Yes
932
+ 1,6000,5500,1,60.0,40000,4000.0,3.0,1,47,8000,0,1,1,0,1,1,No
933
+ 1,2000,1500,0,30.0,1700,200.0,6.0,1,34,3000,1,0,0,0,1,0,No
934
+ 1,3000,2000,1,20.0,4000,500.0,5.0,1,56,1100,1,0,1,0,1,0,No
935
+ 1,2500,2500,0,30.0,10000,1800.0,2.0,3,35,4000,1,1,1,0,5,0,Yes
936
+ 1,5000,5000,0,30.0,9000,1200.0,9.0,1,36,1000,1,0,1,0,1,0,Yes
937
+ 1,2000,2000,0,60.0,8000,850.0,3.5,1,40,8000,0,0,0,0,3,0,Yes
938
+ 0,4000,4000,0,30.0,19000,9000.0,2.0,1,46,7000,0,1,1,0,5,1,Yes
939
+ 0,9000,9000,0,,5000,320.0,9.0,4,38,9000,1,1,1,1,1,1,Yes
940
+ 1,8000,8000,0,36.0,2800,300.0,11.0,2,49,9000,1,0,1,0,2,0,Yes
941
+ 1,6000,5000,1,15.0,9000,450.0,3.0,1,26,5000,0,0,1,1,1,0,No
942
+ 1,200,200,0,15.0,8700,1200.0,3.0,2,26,1200,1,1,1,0,5,0,Yes
943
+ 1,15000,8000,1,30.0,7000,330.0,1.5,1,33,8000,0,1,0,1,4,0,No
944
+ 0,1500,1000,1,24.0,2000,450.0,2.0,1,42,1200,0,0,1,1,4,0,No
945
+ 1,1500,1500,0,30.0,2500,655.0,4.0,1,32,10000,0,0,0,0,1,0,Yes
946
+ 1,5000,5000,0,30.0,6000,1300.0,6.0,1,47,1000,1,0,0,0,1,0,Yes
947
+ 1,2000,2000,0,30.0,2000,800.0,3.0,1,42,4000,0,0,1,0,1,0,Yes
948
+ 1,800,400,1,15.0,7000,800.0,20.0,3,51,800,0,1,1,0,1,0,No
949
+ 0,10000,7000,1,30.0,4000,400.0,8.0,4,60,9000,1,0,1,1,4,1,No
950
+ 0,4000,2000,1,30.0,12000,6000.0,3.0,1,52,7000,0,1,1,0,5,1,No
951
+ 1,2000,2000,0,30.0,2000,500.0,2.0,3,34,3000,0,0,1,1,4,0,Yes
952
+ 0,800,800,0,36.0,5000,400.0,3.0,1,33,2000,0,0,0,1,4,0,Yes
953
+ 1,6000,6000,0,60.0,9500,900.0,7.0,2,28,9000,1,1,1,1,3,0,Yes
954
+ 1,400,400,0,30.0,9000,200.0,1.0,2,27,4000,0,0,0,1,4,0,Yes
955
+ 0,20000,12000,1,36.0,35000,6000.0,3.0,1,35,9000,0,1,0,1,3,1,No
956
+ 1,5000,5000,0,30.0,7000,3000.0,7.0,1,27,1000,0,0,1,1,4,0,Yes
957
+ 1,1500,1000,1,15.0,3000,4000.0,4.0,1,33,5000,0,0,1,0,1,0,No
958
+ 1,10000,7000,1,30.0,9000,5000.0,4.0,3,34,8000,0,1,1,1,4,0,No
959
+ 0,1000,1000,0,30.0,12000,800.0,6.0,1,40,3000,0,0,1,0,1,0,Yes
960
+ 0,3000,3000,0,60.0,5000,245.0,3.0,2,42,5000,1,0,0,0,2,0,Yes
961
+ 1,3000,3000,0,30.0,3000,330.0,5.0,3,44,4000,1,1,0,1,4,0,Yes
962
+ 1,1500,1500,0,60.0,2500,255.0,3.0,3,36,6000,0,0,1,0,5,0,Yes
963
+ 1,1200,1200,0,30.0,3200,480.0,3.0,1,47,9000,0,0,1,0,1,0,Yes
964
+ 1,5000,1000,1,60.0,5000,700.0,1.0,1,38,2000,0,0,0,1,1,0,No
965
+ 1,5000,5000,0,30.0,7000,1000.0,2.0,3,30,6000,0,0,0,0,2,0,Yes
966
+ 0,7000,5000,1,30.0,1200,180.0,10.0,3,40,6000,1,1,1,1,4,0,No
967
+ 1,2000,2000,0,60.0,10000,500.0,7.0,1,47,5000,1,0,1,1,5,0,Yes
968
+ 0,10000,10000,0,36.0,14000,925.0,2.0,1,43,12000,1,0,1,1,1,0,Yes
969
+ 0,12000,7000,1,30.0,11000,700.0,1.5,3,39,8000,1,1,0,1,4,0,No
970
+ 1,7000,5000,1,60.0,900,190.0,1.0,2,43,4000,0,1,0,0,4,0,No
971
+ 1,5000,5000,0,30.0,1000,180.0,10.0,4,40,7000,0,0,1,1,3,1,Yes
972
+ 0,10000,7000,1,30.0,4000,400.0,8.0,4,60,9000,1,0,1,1,4,1,No
973
+ 1,3000,2000,1,30.0,5000,1600.0,3.0,1,41,4000,0,0,0,0,5,0,No
974
+ 1,2000,2000,0,30.0,4000,480.0,2.0,1,35,1500,0,0,1,1,4,0,Yes
975
+ 0,800,800,0,36.0,4500,250.0,2.0,2,36,3500,0,1,0,0,3,0,Yes
976
+ 0,2000,2000,0,30.0,7800,800.0,4.0,1,44,5000,1,0,1,0,3,0,Yes
977
+ 0,300,300,0,15.0,4000,250.0,2.0,1,39,1000,1,1,1,0,5,1,Yes
978
+ 0,1300,1300,0,60.0,340,514.0,6.0,3,30,2000,0,0,1,1,5,0,Yes
979
+ 1,5000,5000,0,30.0,3600,2500.0,5.0,2,30,9500,0,1,1,0,4,0,Yes
980
+ 0,1500,1500,0,30.0,11000,600.0,5.0,1,39,7000,0,1,1,1,5,1,Yes
981
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
982
+ 0,1500,1000,1,30.0,3400,120.0,3.0,2,25,7000,0,1,0,0,1,0,No
983
+ 0,5000,5000,0,30.0,4000,200.0,3.0,3,30,5000,1,0,1,1,5,0,Yes
984
+ 0,2000,1500,1,30.0,3000,300.0,5.0,1,36,1200,0,0,1,0,1,0,No
985
+ 1,5000,2000,1,30.0,4500,1300.0,6.0,1,43,3000,1,0,1,0,1,0,No
986
+ 1,5000,5000,0,30.0,1000,180.0,10.0,4,40,7000,0,0,1,1,3,1,Yes
987
+ 0,300,300,0,20.0,6000,260.0,3.0,1,46,1000,0,0,0,0,1,0,Yes
988
+ 0,1500,1500,0,30.0,10000,4800.0,3.0,1,39,3000,0,1,0,1,5,1,Yes
989
+ 1,5000,5000,0,30.0,1000,180.0,10.0,4,40,7000,0,0,1,1,3,1,Yes
990
+ 0,1000,700,1,36.0,2000,140.0,2.0,1,30,1000,0,0,1,0,1,0,No
991
+ 0,3000,1500,1,36.0,3000,500.0,4.0,3,44,1000,0,0,1,0,1,0,No
992
+ 1,500,300,1,60.0,3000,140.0,3.0,1,36,3000,0,0,1,1,1,0,No
993
+ 0,900,900,0,60.0,10000,700.0,4.0,1,36,4000,1,1,1,0,5,1,Yes
994
+ 1,800,400,1,15.0,7700,600.0,3.0,1,39,500,1,1,1,0,1,0,No
995
+ 0,400,400,0,20.0,8000,1000.0,4.0,1,26,3000,0,0,0,0,1,0,Yes
996
+ 0,8000,5000,1,60.0,6000,300.0,2.0,3,30,8000,0,1,0,0,5,0,No
997
+ 0,3000,3000,0,30.0,14000,2800.0,1.0,1,34,5000,0,1,1,1,5,1,Yes
998
+ 0,6000,6000,0,60.0,18000,7000.0,3.0,1,40,7000,1,1,1,1,3,1,Yes
999
+ 0,4000,4000,0,20.0,8000,1000.0,5.0,1,54,1500,0,0,1,0,1,0,Yes
1000
+ 1,7000,5000,1,60.0,5000,650.0,3.0,3,47,6000,1,1,1,0,4,0,No
1001
+ 0,1000,1000,0,20.0,2000,300.0,1.0,1,34,1000,0,0,1,0,1,0,Yes
1002
+ 1,6000,6000,0,60.0,9500,900.0,7.0,2,28,9000,1,1,1,1,3,0,Yes
1003
+ 1,250,200,1,15.0,5000,600.0,6.0,1,28,4000,0,0,0,1,5,0,No
1004
+ 0,7000,7000,0,30.0,19000,8000.0,7.0,1,47,10000,0,1,0,1,3,1,Yes
1005
+ 0,1500,1500,0,30.0,2000,100.0,6.0,1,42,2000,0,0,1,0,2,0,Yes
1006
+ 0,8000,8000,0,30.0,2700,400.0,5.0,1,45,4000,0,0,0,0,5,0,Yes
1007
+ 0,5000,4500,1,30.0,1400,6000.0,4.0,3,43,8000,1,1,0,1,3,1,No
1008
+ 1,600,600,0,15.0,2500,370.0,5.0,3,35,3500,0,0,1,1,1,0,Yes
1009
+ 1,600,600,0,60.0,2000,250.0,5.0,1,30,7000,1,1,1,0,1,0,Yes
1010
+ 1,400,400,0,36.0,8000,890.0,5.0,1,31,4000,0,0,1,1,1,0,Yes
1011
+ 1,4000,1500,1,30.0,3500,720.0,6.0,1,32,15000,0,0,0,0,1,0,No
1012
+ 1,500,500,0,30.0,5700,400.0,8.0,3,34,4000,0,0,1,1,5,0,Yes
1013
+ 1,1000,1000,0,30.0,4000,900.0,8.0,2,30,10000,0,0,0,1,5,0,Yes
1014
+ 0,5000,5000,0,15.0,2800,300.0,7.0,2,36,5000,1,0,0,1,4,0,Yes
1015
+ 1,6000,3000,1,36.0,1800,344.0,3.0,1,24,20000,1,0,1,1,4,0,No
1016
+ 1,500,500,0,15.0,1000,180.0,2.0,1,34,4000,0,0,1,0,1,0,Yes
1017
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
1018
+ 0,8000,5000,1,60.0,6000,300.0,2.0,3,30,8000,0,1,0,0,2,0,No
1019
+ 1,1500,1500,0,30.0,1420,444.0,5.0,1,25,1500,0,1,0,0,1,0,Yes
1020
+ 0,1000,1000,0,30.0,2000,700.0,2.0,1,50,2000,0,0,0,0,1,0,Yes
1021
+ 0,5000,5000,0,15.0,3100,300.0,6.0,2,46,3000,0,0,0,1,4,0,Yes
1022
+ 1,1000,1000,0,36.0,2000,300.0,2.0,1,50,3500,0,0,1,0,1,0,Yes
1023
+ 1,400,400,0,15.0,1000,400.0,5.0,1,35,5000,0,0,0,1,5,0,Yes
1024
+ 0,1600,1600,0,60.0,4500,150.0,3.0,2,35,4000,0,0,1,0,3,0,Yes
1025
+ 0,7500,7500,0,60.0,14000,165.0,3.0,3,40,20000,1,0,1,1,4,0,Yes
1026
+ 0,2000,2000,0,40.0,3000,600.0,2.0,1,42,3000,1,0,0,1,1,0,Yes
1027
+ 0,500,500,0,30.0,7000,400.0,7.0,1,44,5000,1,0,1,0,1,0,Yes
1028
+ 1,5000,1000,1,60.0,7900,850.0,1.0,1,41,4000,1,0,0,1,5,0,No
1029
+ 1,600,500,1,15.0,1000,250.0,4.0,1,29,4000,0,1,0,1,5,0,No
1030
+ 1,1000,1000,0,30.0,15000,256.0,6.0,3,22,2000,1,0,1,1,4,0,Yes
1031
+ 1,2000,1000,1,12.0,9000,850.0,2.0,3,40,2000,1,0,1,0,4,0,No
1032
+ 0,1000,1000,0,30.0,2500,100.0,8.0,1,36,4000,0,0,1,1,2,0,Yes
1033
+ 1,7000,5000,1,60.0,5000,650.0,3.0,3,47,6000,1,1,1,0,4,0,No
1034
+ 1,600,600,0,20.0,1200,120.0,2.0,1,45,2000,0,0,1,0,1,0,Yes
1035
+ 0,1000,1000,0,15.0,3000,400.0,12.0,1,26,3000,0,0,0,0,1,0,Yes
1036
+ 0,6000,5000,1,30.0,25000,3000.0,4.0,1,41,9000,0,1,1,1,3,1,No
1037
+ 1,1000,1000,0,36.0,18000,1400.0,2.0,1,46,4900,0,1,1,1,5,1,Yes
1038
+ 1,12000,10000,1,60.0,8000,600.0,5.0,1,40,8000,1,0,0,0,3,0,No
1039
+ 1,4000,3000,1,30.0,5000,300.0,3.0,1,30,2000,0,0,1,0,1,0,No
1040
+ 1,1000,1000,0,30.0,7000,600.0,1.0,1,34,5000,0,1,0,1,5,1,Yes
1041
+ 1,3000,3000,0,30.0,6500,870.0,4.0,1,30,1500,0,0,0,0,1,0,Yes
1042
+ 0,2500,2500,0,60.0,12500,0.0,0.0,2,46,10000,0,0,0,0,1,0,Yes
1043
+ 0,2000,2000,0,30.0,3000,720.0,2.0,1,35,2000,1,0,1,0,1,0,Yes
1044
+ 0,1000,1000,0,30.0,2500,500.0,4.0,1,45,6300,0,0,0,1,1,0,Yes
1045
+ 1,4000,4000,0,30.0,3250,400.0,9.0,2,44,5000,1,1,1,1,4,0,Yes
1046
+ 1,1000,1000,0,50.0,3000,150.0,5.0,2,31,10000,0,0,1,0,1,0,Yes
1047
+ 0,1000,1000,0,30.0,9000,1000.0,7.0,3,27,1000,1,1,1,0,1,0,Yes
1048
+ 1,1000,1000,0,30.0,2000,500.0,5.0,1,36,4000,0,0,1,0,1,0,Yes
1049
+ 0,4000,4000,0,60.0,9000,1200.0,4.0,1,44,5000,0,0,1,1,5,0,Yes
1050
+ 1,5000,5000,0,30.0,9000,2500.0,6.0,1,37,1300,0,0,1,0,1,0,Yes
1051
+ 0,1000,1000,0,30.0,2000,700.0,9.0,3,31,2000,0,0,0,1,5,0,Yes
1052
+ 0,1500,1000,1,60.0,3000,245.0,9.0,3,33,2000,1,0,1,1,5,0,No
1053
+ 0,2000,2000,0,30.0,25000,1200.0,8.0,1,35,25000,0,0,0,0,1,0,Yes
1054
+ 1,8000,5000,1,30.0,4600,350.0,2.0,2,29,6000,0,0,1,1,4,0,No
1055
+ 1,5000,3000,1,30.0,5000,700.0,2.0,1,33,5000,1,0,1,0,1,0,No
1056
+ 1,4000,4000,0,30.0,5000,550.0,5.0,3,42,1800,0,0,0,1,4,0,Yes
1057
+ 1,2000,2000,0,30.0,2000,800.0,1.0,1,32,3000,1,0,0,0,1,0,Yes
1058
+ 1,4000,1000,1,60.0,8000,1000.0,2.0,1,42,4000,1,0,0,0,5,0,No
1059
+ 1,300,300,0,30.0,1800,200.0,9.0,3,28,1600,0,0,0,1,1,0,Yes
1060
+ 1,600,600,0,24.0,1500,318.0,4.0,1,27,10000,0,0,1,1,4,0,Yes
1061
+ 1,700,700,0,60.0,4000,300.0,21.0,1,46,4000,0,1,0,0,1,0,Yes
1062
+ 0,5000,5000,0,30.0,18000,6000.0,6.0,3,48,5000,0,1,0,0,5,1,Yes
1063
+ 0,10000,8000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,No
1064
+ 0,1000,1000,0,30.0,3100,300.0,28.0,2,50,2000,1,0,0,1,4,0,Yes
1065
+ 0,2000,2000,0,30.0,2750,750.0,6.0,1,26,1500,0,0,1,0,1,0,Yes
1066
+ 0,1200,1200,0,30.0,7000,604.0,5.0,3,38,2000,1,0,1,1,5,0,Yes
1067
+ 0,1500,1500,0,30.0,3500,688.0,5.0,1,28,15000,0,0,0,1,5,0,Yes
1068
+ 0,10000,8000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,No
1069
+ 1,5000,5000,0,30.0,1000,120.0,5.0,3,35,7000,0,1,1,0,2,0,Yes
1070
+ 0,5000,2000,1,60.0,8000,2000.0,3.0,3,42,4000,1,0,1,1,4,0,No
1071
+ 1,1000,1000,0,36.0,6000,500.0,7.0,1,39,3000,0,0,1,1,4,0,Yes
1072
+ 0,2000,2000,0,30.0,3500,200.0,3.0,2,49,5000,0,0,1,1,5,0,Yes
1073
+ 1,10000,10000,0,60.0,12000,1300.0,12.0,1,45,10000,0,0,1,1,1,0,Yes
1074
+ 0,3000,3000,0,30.0,4500,150.0,3.0,1,46,5000,0,0,1,1,5,0,Yes
1075
+ 1,8000,8000,0,60.0,4000,450.0,3.0,3,43,7000,0,0,1,0,3,0,Yes
1076
+ 0,12000,12000,0,60.0,30000,240.0,15.0,3,41,45000,1,0,0,0,4,0,Yes
1077
+ 1,2000,2000,0,60.0,2600,300.0,3.0,3,42,8000,0,1,1,0,5,0,Yes
1078
+ 1,1000,1000,0,30.0,1000,500.0,4.0,3,36,4500,0,0,1,1,5,0,Yes
1079
+ 1,1500,1500,0,60.0,2500,270.0,4.0,3,46,6000,0,1,0,0,5,0,Yes
1080
+ 1,2000,2000,0,30.0,10000,700.0,6.0,1,36,10000,0,0,1,0,4,0,Yes
1081
+ 0,1500,1500,0,30.0,3000,360.0,2.0,1,42,2000,0,0,0,0,1,0,Yes
1082
+ 1,2000,2000,0,30.0,1000,720.0,2.0,2,32,3000,0,0,1,1,4,0,Yes
1083
+ 1,9000,7000,1,,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
1084
+ 0,7500,7500,0,60.0,5000,625.0,8.0,1,52,8000,0,0,0,0,2,0,Yes
1085
+ 1,2500,2500,0,60.0,4000,450.0,7.0,1,39,1000,0,0,1,1,4,0,Yes
1086
+ 1,8000,8000,0,36.0,2800,300.0,11.0,2,49,9000,1,0,1,0,2,0,Yes
1087
+ 1,2000,2000,0,30.0,6500,700.0,3.0,1,47,5000,0,0,0,1,4,0,Yes
1088
+ 1,200,200,0,30.0,3000,400.0,5.0,1,35,600,0,0,0,0,1,0,Yes
1089
+ 0,1000,1000,0,15.0,3000,500.0,7.0,2,38,5000,0,0,0,1,3,0,Yes
1090
+ 1,2000,2000,0,60.0,9000,750.0,1.0,1,39,5000,0,0,1,0,1,0,Yes
1091
+ 1,3000,3000,0,15.0,6000,450.0,5.0,1,35,4000,0,0,1,0,1,0,Yes
1092
+ 0,9000,9000,0,36.0,10000,900.0,3.0,3,35,9000,1,0,0,1,4,1,Yes
1093
+ 1,500,500,0,15.0,2800,560.0,4.0,3,38,2500,0,0,1,1,4,0,Yes
1094
+ 0,2000,2000,0,30.0,2000,800.0,3.0,1,31,2000,0,0,0,0,1,0,Yes
1095
+ 1,1500,900,1,30.0,2500,400.0,3.0,1,33,2500,1,0,1,0,5,0,No
1096
+ 1,600,600,0,60.0,3000,145.0,25.0,1,50,3000,1,1,1,0,1,0,Yes
1097
+ 1,10000,10000,0,60.0,10000,4000.0,4.0,1,47,10000,1,0,1,1,5,0,Yes
1098
+ 1,1000,1000,0,75.0,2670,295.0,3.0,1,25,1500,0,1,1,1,1,0,Yes
1099
+ 1,500,500,0,15.0,1000,250.0,3.0,1,32,5000,0,0,1,0,5,0,Yes
1100
+ 1,500,500,0,30.0,4000,400.0,5.0,1,37,1000,0,0,0,0,1,0,Yes
1101
+ 1,5000,5000,0,,7000,1000.0,2.0,3,30,6000,1,0,0,0,2,0,Yes
1102
+ 0,10000,8000,1,60.0,10000,1000.0,10.0,3,40,8000,1,1,1,1,4,0,No
1103
+ 0,1500,1200,0,60.0,2890,630.0,5.0,1,40,1500,0,0,1,0,1,0,No
1104
+ 1,5000,5000,0,30.0,3000,350.0,16.0,3,62,6000,0,0,0,0,4,0,Yes
1105
+ 0,9000,9000,1,60.0,10000,650.0,5.0,1,49,12000,1,0,0,0,2,0,Yes
1106
+ 1,6000,6000,0,30.0,3500,400.0,7.0,1,47,3000,0,0,1,0,1,0,Yes
1107
+ 1,5000,5000,0,30.0,7000,1000.0,2.0,3,30,6000,1,0,0,0,2,0,Yes
1108
+ 0,4000,4000,0,30.0,10000,400.0,6.0,2,43,7000,0,0,0,1,3,0,Yes
1109
+ 0,5000,5000,0,30.0,1000,250.0,5.0,3,35,7000,0,1,1,0,2,0,Yes
1110
+ 1,3000,2500,1,60.0,7450,971.0,7.0,3,33,3000,1,1,0,1,5,0,No
1111
+ 0,5000,4000,0,30.0,8000,880.0,9.0,3,34,6000,1,0,0,0,5,0,No
1112
+ 1,2000,2000,0,60.0,38000,1400.0,2.0,1,48,7000,0,1,0,1,5,1,Yes
1113
+ 1,3000,1000,1,60.0,7000,600.0,4.0,1,38,4000,1,0,0,0,5,0,No
1114
+ 1,1000,600,1,30.0,1200,100.0,2.0,3,29,2000,0,0,1,0,1,0,No
1115
+ 1,2500,2500,0,36.0,10000,500.0,7.0,1,34,6000,0,0,0,0,3,0,Yes
1116
+ 1,4000,3500,1,25.0,7500,251.0,3.0,1,43,11000,1,0,1,1,1,0,No
1117
+ 1,2000,2000,0,30.0,2600,665.0,2.0,1,35,1500,1,0,1,0,1,0,Yes
1118
+ 1,5000,2500,1,36.0,12000,3000.0,3.0,1,39,6000,0,1,1,1,3,1,No
1119
+ 1,2000,2000,0,30.0,3500,720.0,10.0,1,45,4000,0,0,1,1,4,0,Yes
1120
+ 0,8000,8000,0,60.0,10000,256.0,5.0,2,36,12000,0,0,1,0,3,0,Yes
1121
+ 1,1500,1500,0,36.0,3000,360.0,2.0,1,45,2000,1,0,1,1,4,0,Yes
1122
+ 1,5000,5000,0,15.0,2200,400.0,3.0,1,38,2000,0,0,1,1,1,0,Yes
1123
+ 1,4000,4000,0,30.0,3250,400.0,9.0,2,44,5000,1,1,1,1,4,0,Yes
1124
+ 0,8000,8000,0,60.0,19000,12000.0,5.0,3,46,9000,0,1,1,1,3,1,Yes
1125
+ 0,1000,1000,0,30.0,7000,409.0,3.0,1,25,5000,1,1,0,0,1,0,Yes
1126
+ 0,10000,10000,0,60.0,12000,1200.0,12.0,1,37,9000,0,0,1,0,2,0,Yes
1127
+ 1,10000,8000,1,60.0,1000,5000.0,3.0,3,32,20000,1,1,1,0,4,0,No
1128
+ 0,1000,1000,0,30.0,5000,120.0,6.0,1,33,4000,0,0,1,0,1,0,Yes
1129
+ 1,600,600,0,30.0,7000,670.0,7.0,3,32,3000,0,0,1,1,5,0,Yes
1130
+ 1,450,400,1,60.0,1500,100.0,10.0,1,35,1500,0,1,0,0,4,0,No
1131
+ 1,3000,3000,0,30.0,5000,500.0,4.0,1,39,5000,0,0,1,0,2,0,Yes
1132
+ 1,2600,2600,0,30.0,15000,690.0,5.0,1,40,2000,1,0,1,1,1,0,Yes
1133
+ 0,5000,4000,1,60.0,10000,400.0,5.0,2,36,7000,0,0,0,0,3,0,No
1134
+ 1,1200,1200,0,60.0,6000,620.0,8.0,1,42,4000,0,1,0,1,4,0,Yes
1135
+ 0,1000,1000,0,30.0,700,150.0,3.0,3,24,5000,1,0,1,1,5,0,Yes
1136
+ 1,8000,8000,0,60.0,4000,450.0,3.0,3,43,7000,0,0,1,0,3,0,Yes
1137
+ 1,2000,2000,0,30.0,2000,580.0,1.0,2,38,1000,1,0,0,0,3,0,Yes
1138
+ 1,1000,1000,0,30.0,2500,555.0,3.0,1,27,15000,0,0,1,1,4,0,Yes
1139
+ 0,2000,2000,0,30.0,3000,380.0,9.0,1,39,3000,1,0,1,1,4,0,Yes
1140
+ 0,1500,1500,0,20.0,5000,480.0,3.0,1,22,2000,0,1,1,0,1,0,Yes
1141
+ 1,7000,5000,1,60.0,5000,650.0,3.0,3,47,6000,1,1,1,0,4,0,No
1142
+ 1,2000,1000,1,30.0,5000,1000.0,1.0,1,36,4000,1,0,0,1,5,0,No
1143
+ 0,300,300,0,20.0,1000,0.0,0.0,3,28,2500,0,0,1,1,5,0,Yes
1144
+ 0,3000,2000,1,12.0,2000,250.0,6.0,1,29,4000,0,1,0,0,1,0,No
1145
+ 0,1000,1000,0,30.0,2000,150.0,4.0,1,32,4500,0,0,1,0,1,0,Yes
1146
+ 1,4000,4000,0,30.0,3250,400.0,9.0,2,44,5000,1,1,1,1,4,0,Yes
1147
+ 0,9000,9000,0,30.0,5000,320.0,9.0,4,38,9000,1,1,1,1,1,1,Yes
1148
+ 1,9000,9000,0,60.0,10000,925.0,2.0,2,39,20000,0,0,1,0,3,0,Yes
1149
+ 0,14000,14000,0,36.0,7000,3000.0,10.0,1,35,7000,0,0,1,0,2,0,Yes
1150
+ 1,8000,8000,0,36.0,2800,300.0,11.0,2,49,9000,1,0,1,0,2,0,Yes
1151
+ 0,2000,1000,1,60.0,5000,889.0,22.0,3,46,2000,0,0,1,1,5,0,No
1152
+ 1,3000,3000,0,30.0,5000,550.0,6.0,3,36,6000,1,0,0,0,5,0,Yes
1153
+ 1,1000,1000,0,30.0,2000,280.0,2.0,1,48,3500,1,0,1,0,1,0,Yes
1154
+ 1,2000,2000,0,30.0,2000,700.0,1.0,1,38,1000,0,0,0,0,1,0,Yes
1155
+ 1,9000,6000,1,30.0,1000,3000.0,2.0,3,38,7000,1,1,1,0,3,0,No
1156
+ 1,2000,2000,0,50.0,3000,500.0,3.0,2,31,10000,0,0,1,0,1,0,Yes
1157
+ 1,700,700,0,60.0,3500,200.0,20.0,3,45,3500,0,1,0,0,4,0,Yes
1158
+ 1,9000,7000,1,45.0,7800,430.0,2.0,2,51,7000,1,0,1,0,4,0,No
1159
+ 1,900,600,1,36.0,1200,120.0,2.0,1,43,1300,0,0,0,0,1,0,No
1160
+ 0,20000,10000,1,60.0,40000,565.0,5.0,1,40,25000,1,0,0,0,2,0,No
1161
+ 1,5000,5000,0,36.0,2000,500.0,17.0,1,42,2000,0,0,1,0,1,0,Yes