Update app.py

app.py

@@ -20,12 +20,12 @@ def fetch_esg_data(company_name):
     if esg_data is not None and not esg_data.empty:
         esg_df = pd.DataFrame(esg_data)
         esg_scores = esg_df.loc[["environmentScore", "socialScore", "governanceScore"], :].dropna().astype(float)
-        
+
         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)
@@ -34,37 +34,50 @@ def fetch_esg_data(company_name):
     else:
         return pd.DataFrame(), None
 
-# Gradio interface
+# Gradio interface with multiple tabs
 def app_interface():
     with gr.Blocks() as app:
-        # Dropdown to select company name
-        company = gr.Dropdown(
-            label="Select Company",
-            choices=list(company_dict.keys()),
-            value="Apple",  # Default value
-            interactive=True  # Make it interactive
-        )
-        
-        # Button to fetch and plot ESG data
-        plot_button = gr.Button("Generate ESG Plot")
-        
-        # LinePlot component for displaying the ESG data
-        line_plot = gr.LinePlot(label="ESG Scores Line Plot", x="ESG Category", y="Score", overlay_point=True)
-        
-        # ScatterPlot component for displaying the ESG data
-        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])
+        gr.Markdown("# ESG Data Explorer")
+
+        with gr.Tab("ESG Data"):
+            # Dropdown to select company name
+            company = gr.Dropdown(
+                label="Select Company",
+                choices=list(company_dict.keys()),
+                value="Apple",  # Default value
+                interactive=True  # Make it interactive
+            )
+
+            # Button to fetch and plot ESG data
+            plot_button = gr.Button("Generate ESG Plot")
+
+            # Dataframe 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])
+
+        with gr.Tab("Tab 2"):
+            gr.Markdown("Content for Tab 2 goes here.")
+            # Add more components relevant to Tab 2
+
+        with gr.Tab("Tab 3"):
+            gr.Markdown("Content for Tab 3 goes here.")
+            # Add more components relevant to Tab 3
+
+        with gr.Tab("Tab 4"):
+            gr.Markdown("Content for Tab 4 goes here.")
+            # Add more components relevant to Tab 4
 
     return app
 
 # Launch the Gradio app
 app = app_interface()
-app.launch()
-
+if __name__ == "__main__":
+    app.launch()