Update app.py

app.py

@@ -87,6 +87,34 @@ def create_bar_plot(df: pd.DataFrame, company_name: str) -> go.Figure:
         template='plotly_white'
     )
     return fig
+def create_pie_chart(df: pd.DataFrame, company_name: str) -> go.Figure:
+    """Create a pie chart using plotly"""
+    total_score = df['Score'].sum()
+    percentages = (df['Score'] / total_score * 100).round(1)
+    
+    # Create labels with both category and percentage
+    labels = [f"{cat} ({pct}%)" for cat, pct in zip(df['ESG Category'], percentages)]
+    
+    fig = go.Figure()
+    fig.add_trace(go.Pie(
+        labels=labels,
+        values=df['Score'],
+        hole=0.4,  # Creates a donut chart
+        marker=dict(
+            colors=['rgb(55, 83, 109)', 'rgb(26, 118, 255)', 'rgb(178, 200, 223)']
+        ),
+        textinfo='label+value',
+        textposition='outside',
+        texttemplate='%{label}<br>Score: %{value:.1f}'
+    ))
+    fig.update_layout(
+        title=f"ESG Score Distribution for {company_name}",
+        height=400,
+        template='plotly_white',
+        showlegend=False
+    )
+    return fig
+
 
 def create_empty_plot(message: str) -> go.Figure:
     """Create an empty plot with an error message"""
@@ -157,34 +185,38 @@ def create_interface() -> gr.Blocks:
                     )
             
             with gr.Row():
-                line_plot = gr.Plot(label="Trend Analysis")
+                with gr.Column():
+                    line_plot = gr.Plot(label="Trend Analysis")
+                with gr.Column():
+                    pie_plot = gr.Plot(label="Distribution Analysis")
             
             with gr.Row():
                 with gr.Column():
-                    scatter_plot = gr.Plot(label="Distribution Analysis")
+                    scatter_plot = gr.Plot(label="Score Distribution")
                 with gr.Column():
-                    bar_plot = gr.Plot(label="Comparison Analysis")
+                    bar_plot = gr.Plot(label="Score Comparison")
             
-            def process_esg_request(company_name: str) -> Tuple[go.Figure, go.Figure, go.Figure, str]:
+            def process_esg_request(company_name: str) -> Tuple[go.Figure, go.Figure, go.Figure, go.Figure, str]:
                 # Fetch the data
                 plot_df, status = fetch_esg_data(company_name)
                 
                 if plot_df is None:
                     empty_plot = create_empty_plot(status)
-                    return empty_plot, empty_plot, empty_plot, status
+                    return empty_plot, empty_plot, empty_plot, empty_plot, status
                 
-                # Create all three plots
+                # Create all plots
                 line = create_line_plot(plot_df, company_name)
                 scatter = create_scatter_plot(plot_df, company_name)
                 bar = create_bar_plot(plot_df, company_name)
+                pie = create_pie_chart(plot_df, company_name)
                 
-                return line, scatter, bar, status
+                return line, pie, scatter, bar, status
             
             # Connect the button click to the process function
             plot_button.click(
                 fn=process_esg_request,
                 inputs=company,
-                outputs=[line_plot, scatter_plot, bar_plot, status_message],
+                outputs=[line_plot, pie_plot, scatter_plot, bar_plot, status_message],
                 api_name="generate_esg_analysis"
             )
         
@@ -198,8 +230,9 @@ def create_interface() -> gr.Blocks:
                 1. Select a company from the dropdown menu
                 2. Click 'Generate ESG Analysis' to view multiple visualizations:
                    - Trend Analysis: Shows the progression across ESG categories
-                   - Distribution Analysis: Displays the spread of ESG scores
-                   - Comparison Analysis: Compares ESG scores side by side
+                   - Distribution Analysis: Shows the relative proportion of each ESG component
+                   - Score Distribution: Displays the spread of ESG scores
+                   - Score Comparison: Compares ESG scores side by side
                 
                 ### Metrics Explained
                 - **Environmental Score**: Measures company's environmental impact and sustainability initiatives