feat: updated app script

app.py

@@ -193,7 +193,6 @@ if page == "Summary":
         inbound_values = [23, 77]  # Adjust the values
         labels = ['Outbound', 'Inbound']
         color_scheme = ['#155F7A', '#29b5e8']
-        title = 'States Migration'
 
         donut_fig = create_donut_chart(inbound_values, labels, color_scheme, title)
         st.plotly_chart(donut_fig, use_container_width=True)
@@ -212,6 +211,11 @@ if page == "Summary":
             '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=400,  # Shrink the height to fit page better
+        )
         st.plotly_chart(fig_cluster, use_container_width=True)
         
         st.markdown('#### Sales by Cluster')
@@ -220,7 +224,7 @@ if page == "Summary":
         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', title="Sales by Cluster")
+        fig_sales = px.bar(df_sales, x='Cluster', y='Sales')
         st.plotly_chart(fig_sales, use_container_width=True)
 
     # Right Column (Blue): Key Metrics Overview and Data Preparation Summary