Update app.py

app.py

@@ -37,18 +37,22 @@ def main():
         "인구밀집도": population_df
     }
     
-    combined_data = pd.concat([dataset_mapping[dataset_name] for dataset_name in datasets])
-    
-    fig, ax = plt.subplots(figsize=(8, 8))
-    
-    centroids, labels = apply_kmeans(combined_data.values, k_value)
-    ax.scatter(combined_data['x'], combined_data['y'], c=labels, cmap='viridis')
-    ax.scatter(centroids[:, 0], centroids[:, 1], s=200, c='red', marker='X')
-    
-    ax.set_xlim(0, 100)
-    ax.set_ylim(0, 100)
-    ax.set_title(f"K-means clustering result (k={k_value})")
-    st.pyplot(fig)
+   # Check if any dataset is selected
+    if datasets:
+        combined_data = pd.concat([dataset_mapping[dataset_name] for dataset_name in datasets])
+        
+        fig, ax = plt.subplots(figsize=(8, 8))
+        
+        centroids, labels = apply_kmeans(combined_data.values, k_value)
+        ax.scatter(combined_data['x'], combined_data['y'], c=labels, cmap='viridis')
+        ax.scatter(centroids[:, 0], centroids[:, 1], s=200, c='red', marker='X')
+        
+        ax.set_xlim(0, 100)
+        ax.set_ylim(0, 100)
+        ax.set_title(f"K-means clustering result (k={k_value})")
+        st.pyplot(fig)
 
 if __name__ == "__main__":
-    main()
+    main()
+
+