commit

app.py

@@ -43,28 +43,43 @@ def get_topics():
         return sorted(df['topic'].dropna().unique().tolist())
     return []
 
-def get_specific_categories():
-    """Get unique specific categories (e.g., PM2.5, NOx, etc.)"""
+def get_specific_categories(topics=None):
+    """Get unique specific categories filtered by topics"""
     if df.empty:
         return []
-    if 'category' in df.columns:
-        return sorted(df['category'].dropna().unique().tolist())
+
+    filtered_df = df
+    if topics and len(topics) > 0:
+        filtered_df = df[df['topic'].isin(topics)]
+
+    if 'category' in filtered_df.columns:
+        return sorted(filtered_df['category'].dropna().unique().tolist())
     return []
 
-def get_locations():
-    """Get unique locations (e.g., Urban, Rural, etc.)"""
+def get_locations(topics=None):
+    """Get unique locations filtered by topics"""
     if df.empty:
         return []
-    if 'location' in df.columns:
-        return sorted(df['location'].dropna().unique().tolist())
+
+    filtered_df = df
+    if topics and len(topics) > 0:
+        filtered_df = df[df['topic'].isin(topics)]
+
+    if 'location' in filtered_df.columns:
+        return sorted(filtered_df['location'].dropna().unique().tolist())
     return []
 
-def get_impacts():
-    """Get unique impact types (e.g., Primary Health, etc.)"""
+def get_impacts(topics=None):
+    """Get unique impact types filtered by topics"""
     if df.empty:
         return []
-    if 'impact' in df.columns:
-        return sorted(df['impact'].dropna().unique().tolist())
+
+    filtered_df = df
+    if topics and len(topics) > 0:
+        filtered_df = df[df['topic'].isin(topics)]
+
+    if 'impact' in filtered_df.columns:
+        return sorted(filtered_df['impact'].dropna().unique().tolist())
     return []
 
 def get_regions():
@@ -264,27 +279,6 @@ def create_box_plot(filtered_df):
     fig.update_layout(xaxis_tickangle=-45, height=600)
     return fig
 
-def get_summary_stats(filtered_df):
-    """Generate summary statistics for filtered data"""
-    if filtered_df.empty:
-        return "No data available for the selected filters"
-
-    stats = filtered_df['value'].describe()
-
-    summary = f"""
-### Summary Statistics
-
-- **Count**: {stats['count']:.0f} data points
-- **Mean**: ${stats['mean']:,.2f}
-- **Median**: ${stats['50%']:,.2f}
-- **Std Dev**: ${stats['std']:,.2f}
-- **Min**: ${stats['min']:,.2f}
-- **Max**: ${stats['max']:,.2f}
-- **25th Percentile**: ${stats['25%']:,.2f}
-- **75th Percentile**: ${stats['75%']:,.2f}
-    """
-
-    return summary
 
 def get_data_table(filtered_df, max_rows=1000):
     """Return filtered data as a dataframe with formatted values"""
@@ -400,11 +394,6 @@ with gr.Blocks(title="GVFD Navigator", theme=gr.themes.Soft()) as demo:
         column_widths=["10%", "12%", "12%", "12%", "12%", "10%", "12%", "10%", "10%"]
     )
 
-    with gr.Row():
-        with gr.Column():
-            gr.Markdown("### Summary Statistics")
-            stats_output = gr.Markdown(value=get_summary_stats(df))
-
     # Visualizations below the table
     gr.Markdown("## Visualizations")
     gr.Markdown("The charts and maps below reflect your filtered data selection from above.")
@@ -560,6 +549,14 @@ with gr.Blocks(title="GVFD Navigator", theme=gr.themes.Soft()) as demo:
     """)
 
     # Event handlers
+    def update_dropdowns_on_topic_change(topics):
+        """Update category, location, and impact dropdowns based on selected topics"""
+        return (
+            gr.Dropdown(choices=get_specific_categories(topics), value=None),
+            gr.Dropdown(choices=get_locations(topics), value=None),
+            gr.Dropdown(choices=get_impacts(topics), value=None)
+        )
+
     def update_all(search, countries, topics, categories, locations, impacts, regions, min_val, max_val):
         """Update all views when filters are applied"""
         # First filter the data
@@ -578,13 +575,19 @@ with gr.Blocks(title="GVFD Navigator", theme=gr.themes.Soft()) as demo:
         # Then pass the filtered dataframe to all visualization functions
         return (
             get_data_table(filtered_df),
-            get_summary_stats(filtered_df),
             create_bar_chart(filtered_df),
             create_map_visualization(filtered_df),
             create_comparison_chart(filtered_df),
             create_box_plot(filtered_df)
         )
 
+    # Wire up topic selector to update dependent dropdowns
+    topic_selector.change(
+        fn=update_dropdowns_on_topic_change,
+        inputs=[topic_selector],
+        outputs=[category_selector, location_selector, impact_selector]
+    )
+
     # Wire up the unified filter button
     refresh_btn.click(
         fn=update_all,
@@ -599,7 +602,7 @@ with gr.Blocks(title="GVFD Navigator", theme=gr.themes.Soft()) as demo:
             min_value,
             max_value
         ],
-        outputs=[data_table, stats_output, bar_chart, map_chart, comparison_chart, box_plot]
+        outputs=[data_table, bar_chart, map_chart, comparison_chart, box_plot]
     )
 
 if __name__ == "__main__":