Update app.py

app.py

@@ -94,6 +94,10 @@ if viz_type == "Complaints by Housing Block and Type":
     block_options = ['All Blocks'] + sorted(data['Housing Block'].unique().tolist())
     selected_block = st.sidebar.selectbox("Select Housing Block", options=block_options)
 
+# Ensure selected_block is only used if defined
+if viz_type == "Complaints by Housing Block and Type" and 'selected_block' not in locals():
+    selected_block = 'All Blocks'  # Default to 'All Blocks' if no selection made
+
 # Filter data based on selected year
 if selected_year != 'All Time':
     filtered_data = data[data['Year Reported'] == selected_year]
@@ -101,7 +105,7 @@ else:
     filtered_data = data  
 
 # Further filter by Housing Block
-if selected_block != 'All Blocks':
+if 'selected_block' in locals() and selected_block != 'All Blocks':
     filtered_data = filtered_data[filtered_data['Housing Block'] == selected_block]
 
 # Filter data based on date range (only for Complaints Over Time visualization)
@@ -122,6 +126,7 @@ st.header(f"Analysis for {'All Time' if selected_year == 'All Time' else selecte
 
 
 
+
 # Display metrics
 col1, col2 = st.columns(2)
 with col1:
@@ -327,7 +332,7 @@ elif viz_type == "Complaints by Housing Block and Type":
     # Plot the data
     fig = complaint_pivot.plot(kind='bar', stacked=True, colormap='inferno', figsize=(10, 6)).get_figure()
     st.pyplot(fig)
-
+    
     st.write("""
     **What this visualization shows:**  
     This line chart shows the trend of complaints over time, displaying the number of complaints reported for each day. It helps identify patterns, peaks, and trends in the complaints data.