Update app.py

app.py

@@ -1,4 +1,4 @@
-import pandas as pd
+'''import pandas as pd
 from sklearn.cluster import KMeans
 import matplotlib.pyplot as plt
 import gradio as gr
@@ -48,4 +48,63 @@ demo = gr.Interface(
     description="Upload a CSV of cities with AvgMonthlyTourists, AvgTemp, and Hotels. Choose number of clusters to group similar cities."
 )
 
+demo.launch()'''
+
+import pandas as pd
+from sklearn.cluster import KMeans
+from sklearn.preprocessing import StandardScaler
+import matplotlib.pyplot as plt
+import gradio as gr
+import tempfile
+
+def cluster_tourism(file, n_clusters):
+    # Load CSV
+    df = pd.read_csv(file)
+
+    # Features to cluster on
+    features = df[['AvgMonthlyTourists', 'AvgTemp', 'Hotels']]
+
+    # Standardize features
+    scaler = StandardScaler()
+    features_scaled = scaler.fit_transform(features)
+
+    # KMeans clustering
+    kmeans = KMeans(n_clusters=n_clusters, random_state=42, n_init=10)
+    df['Cluster'] = kmeans.fit_predict(features_scaled)
+
+    # Save clustered CSV to temporary file
+    tmp_csv = tempfile.NamedTemporaryFile(delete=False, suffix=".csv")
+    df.to_csv(tmp_csv.name, index=False)
+
+    # Plot clusters 
+    plt.figure(figsize=(6,4))
+    for cluster in range(n_clusters):
+        subset = df[df['Cluster'] == cluster]
+        plt.scatter(subset['AvgMonthlyTourists'], subset['AvgTemp'], label=f'Cluster {cluster}')
+    plt.xlabel('Avg Monthly Tourists')
+    plt.ylabel('Avg Temp')
+    plt.title('City Clusters')
+    plt.legend()
+
+    # Save plot to temporary file
+    tmp_plot = tempfile.NamedTemporaryFile(delete=False, suffix=".png")
+    plt.savefig(tmp_plot.name)
+    plt.close()
+
+    return tmp_csv.name, tmp_plot.name
+
+demo = gr.Interface(
+    fn=cluster_tourism,
+    inputs=[
+        gr.File(file_types=[".csv"], type="filepath", label="Upload CSV"),
+        gr.Slider(minimum=2, maximum=10, step=1, label="Number of Clusters")
+    ],
+    outputs=[
+        gr.File(label="CSV with Cluster Labels"),
+        gr.Image(label="Cluster Plot")
+    ],
+    title="City Clustering",
+    description="Upload a CSV of cities with AvgMonthlyTourists, AvgTemp, and Hotels. Choose number of clusters to group similar cities."
+)
+
 demo.launch()