Update app.py

app.py

@@ -202,18 +202,41 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
 
             with gr.Column(scale=3):
                 gr.Markdown("### Visualizations")
-                map_plot = gr.Plot()
-                ts_plot = gr.Plot()
+                # Initialize plots with default values
+                initial_map = create_choropleth_map('crime_total', min_date, max_date)
+                initial_ts = create_time_series_plot('crime_total', min_date, max_date)
+                
+                map_plot = gr.Plot(value=initial_map)
+                ts_plot = gr.Plot(value=initial_ts)
+        
+        # Function to update both plots
+        def update_plots(metric, start_date, end_date):
+            map_fig = create_choropleth_map(metric, start_date, end_date)
+            ts_fig = create_time_series_plot(metric, start_date, end_date)
+            return map_fig, ts_fig
         
+        # Update plots when button is clicked
         update_button.click(
-            fn=create_choropleth_map,
+            fn=update_plots,
             inputs=[metric_selector, start_date_picker, end_date_picker],
-            outputs=map_plot
+            outputs=[map_plot, ts_plot]
         )
-        update_button.click(
-            fn=create_time_series_plot,
+        
+        # Also update plots when any input changes
+        metric_selector.change(
+            fn=update_plots,
+            inputs=[metric_selector, start_date_picker, end_date_picker],
+            outputs=[map_plot, ts_plot]
+        )
+        start_date_picker.change(
+            fn=update_plots,
+            inputs=[metric_selector, start_date_picker, end_date_picker],
+            outputs=[map_plot, ts_plot]
+        )
+        end_date_picker.change(
+            fn=update_plots,
             inputs=[metric_selector, start_date_picker, end_date_picker],
-            outputs=ts_plot
+            outputs=[map_plot, ts_plot]
         )
 
     with gr.Tab("Predictive Analytics"):