feat: updated website

app.py

@@ -199,31 +199,22 @@ if page == "Summary":
     with col2:
         st.markdown('#### 3D Customer Clusters')
         
-        # Replace with your own customer cluster visualization
-        np.random.seed(42)
-        df_cluster = pd.DataFrame({
-            'Cluster': np.random.choice(['Cluster 1', 'Cluster 2', 'Cluster 3', 'Cluster 4'], 100),
-            'x': np.random.randn(100),
-            'y': np.random.randn(100),
-            'z': np.random.randn(100)
-        })
-        fig_cluster = px.scatter_3d(df_cluster, x='x', y='y', z='z', color='Cluster')
-        fig_cluster.update_layout(
-            scene=dict(aspectratio=dict(x=1, y=1, z=0.7)),  # Control the aspect ratio
-            margin=dict(t=0, b=0, l=0, r=0),  # Tighten margins
-            height=300,  # Shrink the height to fit page better
+        # Create 3D PCA plot using actual data from pca_data_5
+        fig_cluster = px.scatter_3d(
+            pca_data_5, 
+            x='PC1', 
+            y='PC2', 
+            z='PC3', 
+            color='cluster_id', 
+            hover_name='CustomerID',
+            title='3D PCA Customer Clusters'
         )
-        st.plotly_chart(fig_cluster, use_container_width=True)
-        
-        st.markdown('#### Sales by Cluster')
-        
-        # Replace with your own sales data
-        sales_data = {'Cluster': ['Cluster 1', 'Cluster 2', 'Cluster 3', 'Cluster 4'],
-                    'Sales': [400000, 600000, 500000, 300000]}
-        df_sales = pd.DataFrame(sales_data)
-        fig_sales = px.bar(df_sales, x='Cluster', y='Sales')
-        fig_sales.update_layout(paper_bgcolor=plot_bgcolor, plot_bgcolor=plot_bgcolor)
-        st.plotly_chart(fig_sales, use_container_width=True)
+        fig_cluster.update_layout(
+        scene=dict(aspectratio=dict(x=1, y=1, z=0.7)),  # Control the aspect ratio
+        margin=dict(t=0, b=0, l=0, r=0),  # Tighten margins
+        height=300,  # Shrink the height to fit page better
+    )
+    st.plotly_chart(fig_cluster, use_container_width=True)
 
     # Right Column (Blue): Key Metrics Overview and Data Preparation Summary
     with col3: