Update app.py

app.py

@@ -1,39 +1,39 @@
 import gradio as gr
 import pandas as pd
 import matplotlib.pyplot as plt
+import seaborn as sns
 
-# Sample population data (you can use a CSV instead)
+# Sample data
 data = {
     "Country": ["India", "China", "USA", "Indonesia", "Brazil"],
     "Population": [1400000000, 1410000000, 331000000, 273000000, 213000000]
 }
 df = pd.DataFrame(data)
+df.set_index("Country", inplace=True)
 
-def plot_chart(countries, chart_type):
-    filtered_df = df[df["Country"].isin(countries)]
-    plt.figure(figsize=(8, 5))
-
-    if chart_type == "Bar":
-        plt.bar(filtered_df["Country"], filtered_df["Population"], color="skyblue")
-        plt.ylabel("Population")
-    else:  # Pie chart
-        plt.pie(filtered_df["Population"], labels=filtered_df["Country"], autopct="%1.1f%%")
-    
-    plt.title("Population by Country")
+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))
+    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_choices = df["Country"].tolist()
+# Country options
+country_choices = df.index.tolist()
 
+# Gradio App
 with gr.Blocks() as demo:
-    gr.Markdown("## 🌍 World Population Chart")
-    with gr.Row():
-        country_select = gr.CheckboxGroup(label="Select Countries", choices=country_choices, value=["India", "China"])
-        chart_type = gr.Radio(label="Chart Type", choices=["Bar", "Pie"], value="Bar")
-    output = gr.Plot()
+    gr.Markdown("## 🌡️ World Population Heatmap")
+    selected = gr.CheckboxGroup(label="Select Countries", choices=country_choices, value=["India", "China", "USA"])
+    out = gr.Plot()
 
-    country_select.change(plot_chart, inputs=[country_select, chart_type], outputs=output)
-    chart_type.change(plot_chart, inputs=[country_select, chart_type], outputs=output)
+    selected.change(fn=generate_heatmap, inputs=selected, outputs=out)
 
 demo.launch()
-