Update app.py

app.py

@@ -13,63 +13,64 @@ company_dict = {
 
 # Function to fetch ESG data for the selected company
 def fetch_esg_data(company_name):
+    # Get the ticker symbol from the company name
     ticker = company_dict[company_name]
+    
+    # Fetch ESG data from Yahoo Finance
     stock = yf.Ticker(ticker)
     esg_data = stock.sustainability
-    if esg_data is not None and not esg_data.empty:
+    
+    # If ESG data is available, process it into a DataFrame
+    if esg_data is not None:
         esg_df = pd.DataFrame(esg_data)
+
+        # Extract only the relevant ESG scores and convert to a DataFrame
         esg_scores = esg_df.loc[["environmentScore", "socialScore", "governanceScore"], :].dropna().astype(float)
+        
+        # Prepare a DataFrame for plotting
         plot_df = pd.DataFrame({
             "ESG Category": ["Environment", "Social", "Governance"],
             "Score": esg_scores.squeeze().values
         })
+        
         # Save the ESG data to a CSV file
         csv_filename = f"{ticker}_esg_data.csv"
         esg_df.to_csv(csv_filename)
-        return plot_df, csv_filename
+
+        return plot_df, csv_filename  # Return the plot DataFrame and the CSV filename
     else:
+        # Return an empty DataFrame and None if no data is available
         return pd.DataFrame(), None
 
-# Gradio interface with a dropdown and file download option
+# Gradio interface with a dropdown for company selection, line plot, scatter plot visualization, and CSV download
 def app_interface():
     with gr.Blocks() as app:
-        gr.Markdown("# ESG Data Explorer")
-        
-        with gr.Tab("ESG Data"):
-            company = gr.Dropdown(
-                label="Select Company",
-                choices=list(company_dict.keys()),  # Show company names
-                value="Apple",  # Default value
-                interactive=True  # Make it interactive
-            )
-            
-            plot_button = gr.Button("Generate ESG Plot")
-            
-            # Graphs for ESG scores
-            line_plot = gr.LinePlot(label="ESG Scores Line Plot", x="ESG Category", y="Score", overlay_point=True)
-            scatter_plot = gr.ScatterPlot(label="ESG Scores Scatter Plot", x="ESG Category", y="Score", overlay_point=True)
-            
-            # File output for CSV download
-            csv_output = gr.File(label="Download CSV")
-            
-            # Define the action when the "Generate ESG Plot" button is clicked
-            plot_button.click(fn=fetch_esg_data, inputs=company, outputs=[line_plot, csv_output, scatter_plot])
-        
-        # Additional tabs for other content
-        with gr.Tab("Tab 2"):
-            gr.Markdown("Content for Tab 2 goes here.")
+        # Dropdown to select company name
+        company = gr.Dropdown(label="Select Company", choices=list(company_dict.keys()), value="Apple")
         
-        with gr.Tab("Tab 3"):
-            gr.Markdown("Content for Tab 3 goes here.")
+        # Button to fetch and plot ESG data
+        plot_button = gr.Button("Generate ESG Plots")
         
-        with gr.Tab("Tab 4"):
-            gr.Markdown("Content for Tab 4 goes here.")
-    
+        # LinePlot component for displaying the ESG data
+        line_plot_output = gr.LinePlot(label="ESG Scores Line Plot", x="ESG Category", y="Score", overlay_point=True)
+
+        # ScatterPlot component for displaying the ESG data
+        scatter_plot_output = gr.ScatterPlot(label="ESG Scores Scatter Plot", x="ESG Category", y="Score", overlay_point=True)
+
+        # Textbox to display messages
+        message = gr.Textbox(label="Message", interactive=False)
+
+        # File output for CSV download
+        csv_output = gr.File(label="Download CSV")
+
+        # Define the action when the "Generate ESG Plot" button is clicked
+        plot_button.click(fn=fetch_esg_data, 
+                          inputs=company, 
+                          outputs=[line_plot_output, scatter_plot_output, csv_output])
+
     return app
 
 # Launch the Gradio app
 app = app_interface()
-if __name__ == "__main__":
-    app.launch()
-
+app.launch()