Create app1.py

app1.py

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+import streamlit as st
+import pandas as pd
+import plotly.express as px
+
+# Set the page layout for Streamlit
+st.set_page_config(layout="wide")
+
+# Title and Introduction
+st.title("Data Visualization App")
+st.markdown(""" 
+    This app allows you to upload a table (CSV or Excel) and ask for graphs to visualize the data.
+    Based on your question, the app will generate interactive graphs using **Plotly**.
+
+    ### Available Features:
+    - **Graph of a column**: Visualize a column as a graph.
+    - **Scatter plot**: Visualize relationships between two columns.
+    
+    Upload your data and ask questions to generate visualizations.
+""")
+
+# File uploader in the sidebar
+file_name = st.sidebar.file_uploader("Upload file:", type=['csv', 'xlsx'])
+
+# File processing and question answering
+if file_name is None:
+    st.markdown('<p class="font">Please upload an excel or csv file </p>', unsafe_allow_html=True)
+else:
+    try:
+        # Check file type and handle reading accordingly
+        if file_name.name.endswith('.csv'):
+            df = pd.read_csv(file_name, sep=';', encoding='ISO-8859-1')  # Adjust encoding if needed
+        elif file_name.name.endswith('.xlsx'):
+            df = pd.read_excel(file_name, engine='openpyxl')  # Use openpyxl to read .xlsx files
+        else:
+            st.error("Unsupported file type")
+            df = None
+
+        if df is not None:
+            numeric_columns = df.select_dtypes(include=['object']).columns
+            for col in numeric_columns:
+                df[col] = pd.to_numeric(df[col], errors='ignore')
+
+            st.write("Original Data:")
+            st.write(df)
+
+            df_numeric = df.copy()
+            df = df.astype(str)
+
+            # Display the first 5 rows of the dataframe in an editable grid
+            st.write("Sample data for graph generation:")
+            st.write(df.head())
+
+    except Exception as e:
+        st.error(f"Error reading file: {str(e)}")
+
+    # User input for the graph query
+    question = st.text_input('Ask your graph-related question')
+
+    with st.spinner():
+        if st.button('Generate Graph'):
+            try:
+                if 'between' in question.lower() and 'and' in question.lower():
+                    # Handle scatter plot (graph between two columns)
+                    columns = question.split('between')[-1].split('and')
+                    columns = [col.strip() for col in columns]
+                    if len(columns) == 2 and all(col in df.columns for col in columns):
+                        fig = px.scatter(df, x=columns[0], y=columns[1], title=f"Scatter Plot between {columns[0]} and {columns[1]}")
+                        st.plotly_chart(fig, use_container_width=True)
+                        st.success(f"Here is the scatter plot between '{columns[0]}' and '{columns[1]}'.")
+                    else:
+                        st.warning("Columns not found in the dataset.")
+                elif 'column' in question.lower():
+                    # Handle graph of a single column
+                    column = question.split('of')[-1].strip()
+                    if column in df.columns:
+                        fig = px.line(df, x=df.index, y=column, title=f"Graph of column '{column}'")
+                        st.plotly_chart(fig, use_container_width=True)
+                        st.success(f"Here is the graph of column '{column}'.")
+                    else:
+                        st.warning(f"Column '{column}' not found in the data.")
+                else:
+                    st.warning("Please ask a valid graph-related question (e.g., 'make a graph between column1 and column2').")
+
+            except Exception as e:
+                st.warning(f"Error processing question or generating graph: {str(e)}")