Update app.py

app.py

@@ -11,29 +11,40 @@ data = {
 df = pd.DataFrame(data)
 df.set_index("Country", inplace=True)
 
+# Heatmap function
 def generate_heatmap(selected_countries):
     filtered_df = df.loc[selected_countries]
-
-    # Normalize for better visualization
     normalized = filtered_df.copy()
     normalized["Population"] = normalized["Population"] / 1e6  # Convert to millions
 
-    plt.figure(figsize=(8, 4))
+    plt.figure(figsize=(6, 3))
     sns.heatmap(normalized.T, annot=True, fmt=".1f", cmap="YlOrRd", cbar_kws={"label": "Population (in millions)"})
     plt.title("🌍 Population Heatmap")
     plt.yticks(rotation=0)
     plt.tight_layout()
     return plt
 
-# Country options
-country_choices = df.index.tolist()
+# Pie chart function
+def generate_pie_chart(selected_countries):
+    filtered_df = df.loc[selected_countries]
+
+    plt.figure(figsize=(5, 5))
+    plt.pie(filtered_df["Population"], labels=filtered_df.index, autopct="%1.1f%%", startangle=90)
+    plt.title("🧩 Population Distribution")
+    plt.tight_layout()
+    return plt
 
 # Gradio App
 with gr.Blocks() as demo:
-    gr.Markdown("## 🌡️ World Population Heatmap")
-    selected = gr.CheckboxGroup(label="Select Countries", choices=country_choices, value=["India", "China", "USA"])
-    out = gr.Plot()
+    gr.Markdown("## 🌍 World Population Visualization")
+    selected = gr.CheckboxGroup(label="Select Countries", choices=df.index.tolist(), value=["India", "China", "USA"])
+
+    with gr.Row():
+        heatmap_output = gr.Plot(label="Heatmap")
+        piechart_output = gr.Plot(label="Pie Chart")
 
-    selected.change(fn=generate_heatmap, inputs=selected, outputs=out)
+    # Link input to both outputs
+    selected.change(fn=generate_heatmap, inputs=selected, outputs=heatmap_output)
+    selected.change(fn=generate_pie_chart, inputs=selected, outputs=piechart_output)
 
 demo.launch()