Update app.py

app.py

@@ -28,27 +28,27 @@ def apply_kmeans(data, k):
 def main():
     st.title("K-means Clustering Simulator")
     
-    dataset = st.selectbox("Choose a dataset:", ["", "교통접근성", "자연환경", "인구밀집도"])
+    datasets = st.multiselect("Choose datasets:", ["교통접근성", "자연환경", "인구밀집도"])
     k_value = st.slider("Select k value:", 1, 10)
     
-    data = None
-    if dataset == "교통접근성":
-        data = traffic_df
-    elif dataset == "자연환경":
-        data = nature_df
-    elif dataset == "인구밀집도":
-        data = population_df
-
-    if data is not None:
+    dataset_mapping = {
+        "교통접근성": traffic_df,
+        "자연환경": nature_df,
+        "인구밀집도": population_df
+    }
+    
+    fig, ax = plt.subplots(figsize=(8, 8))
+    for dataset_name in datasets:
+        data = dataset_mapping[dataset_name]
         centroids, labels = apply_kmeans(data.values, k_value)
         
-        fig, ax = plt.subplots(figsize=(8, 8))
-        ax.scatter(data['x'], data['y'], c=labels, cmap='viridis')
+        ax.scatter(data['x'], data['y'], label=dataset_name, 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 for {dataset} Dataset (k={k_value})")
-        st.pyplot(fig)
+    ax.set_xlim(0, 100)
+    ax.set_ylim(0, 100)
+    ax.set_title(f"K-means clustering result (k={k_value})")
+    ax.legend()
+    st.pyplot(fig)
 
 if __name__ == "__main__":
-    main()
+    main()