Update app.py

app.py

@@ -620,13 +620,30 @@ elif viz_type == "Complaints by Housing Block and Type":
 elif viz_type == "Complaints by Housing Block and Type (Incorporating Suggestions Based on Professor's Feedback)":
     st.subheader("Complaints by Housing Block and Type - Incorporating Suggestions Based on Professor's Feedback")
     
-    # Filtering the data based on the selected year and housing block
-    filtered_data_time = data  # Use filtered_data if date range is not needed
+    # Filtering the data based on the selected year
+    filtered_data_time = data.copy()  # Use filtered_data if date range is not needed
     if selected_year != 'All Time':
         filtered_data_time = filtered_data_time[filtered_data_time['Year Reported'] == selected_year]
-    
+
+    # Define available blocks (up to '3300 block')
+    available_blocks = [
+        '1 block', '100 block', '200 block', '300 block', '400 block', '500 block',
+        '600 block', '700 block', '800 block', '900 block', '1000 block', 
+        '1100 block', '1200 block', '1300 block', '1400 block', '1500 block', 
+        '1600 block', '1700 block', '1800 block', '1900 block', 
+        '2000 block', '2100 block', '2200 block', '2300 block',
+        '2400 block', '2500 block', '2600 block', 
+        '2700 block', '2800 block', '2900 block',
+        '3000 block', '3100 block', 
+        '3200 block', '3300 block'
+    ]
+
+    # Ensure selected_block is in available_blocks
+    if selected_block not in available_blocks:
+        selected_block = None  # or set to a default value
+
     # Further filtering by Housing Block (if applicable)
-    if selected_block != 'All Blocks':
+    if selected_block and selected_block != 'All Blocks':
         filtered_data_time = filtered_data_time[filtered_data_time['Housing Block'] == selected_block]
     
     # Pivoting the data based on the filtered data
@@ -642,15 +659,7 @@ elif viz_type == "Complaints by Housing Block and Type (Incorporating Suggestion
     complaint_pivot = complaint_pivot.astype(float)
 
     # Desired order for the housing blocks (up to '3300 block')
-    desired_order = [
-        '1 block', '100 block', '200 block', '300 block', '400 block', '500 block',
-        '600 block', '700 block', '800 block', '900 block', '1000 block', '1100 block',
-        '1200 block', '1300 block', '1400 block', '1500 block', '1600 block', 
-        '1700 block', '1800 block', '1900 block', '2000 block', '2100 block', 
-        '2200 block', '2300 block', '2400 block', '2500 block', '2600 block', 
-        '2700 block', '2800 block', '2900 block', '3000 block', '3100 block', 
-        '3200 block', '3300 block'
-    ]
+    desired_order = available_blocks
 
     # Reordering the index of the pivot table according to the desired order
     complaint_pivot = complaint_pivot.reindex(desired_order)
@@ -661,7 +670,7 @@ elif viz_type == "Complaints by Housing Block and Type (Incorporating Suggestion
     # Plotting the data
     fig, ax = plt.subplots(figsize=(10, 6))
     
-    if selected_block != 'All Blocks':
+    if selected_block and selected_block != 'All Blocks':
         # Only show the selected housing block
         complaint_pivot.loc[[selected_block]].plot(kind='bar', stacked=True, colormap='inferno', ax=ax)
         
@@ -674,18 +683,20 @@ elif viz_type == "Complaints by Housing Block and Type (Incorporating Suggestion
         complaint_pivot.plot(kind='bar', stacked=True, colormap='inferno', ax=ax)
 
     # Adding percentage labels to the plot
-    for idx, block in enumerate(complaint_pivot.index):
+    for idx, (block, row) in enumerate(complaint_pivot.iterrows()):
         cumulative_height = 0
-        for i, complaint_type in enumerate(complaint_pivot.columns):
-            count = complaint_pivot.iloc[idx, i]
-            percent = percentages.iloc[idx, i]
+        for i, complaint_type in enumerate(row):
+            count = row[i]
+            percent = percentages.loc[block, complaint_type] if count > 0 else 0
+            
             if count > 0:
                 # Compute the position for the percentage label within each segment
-                x_pos = idx  # Adjusted to ensure it aligns with bar positions
+                x_pos = idx if selected_block is None else 0  # Adjust x position based on selection
                 y_pos = cumulative_height + count / 2  # Center within each segment
+                
                 ax.text(
                     x_pos, y_pos, f"{percent:.1f}%", 
-                    ha='center', va='center', 
+                    ha='center', va='center',
                     fontsize=10, color='black',
                     bbox=dict(facecolor='white', alpha=0.7, edgecolor='none')
                 )