Update app.py

app.py

@@ -288,8 +288,9 @@ elif viz_type == "Complaints Over Time":
 elif viz_type == "Complaints by Housing Block and Type":
     st.subheader("Complaints by Housing Block and Type")
     
+    # Filter the data based on the selected block
     if selected_block != 'All Blocks':
-        complaint_pivot = filtered_data_time.pivot_table(
+        complaint_pivot = filtered_data_time[filtered_data_time['Housing Block'] == selected_block].pivot_table(
             index='Housing Block',
             columns='Type of Complaint',
             values='Disposition',
@@ -297,7 +298,7 @@ elif viz_type == "Complaints by Housing Block and Type":
             fill_value=0
         )
     else:
-        complaint_pivot = filtered_data.pivot_table(
+        complaint_pivot = filtered_data_time.pivot_table(
             index='Housing Block',
             columns='Type of Complaint',
             values='Disposition',
@@ -305,9 +306,13 @@ elif viz_type == "Complaints by Housing Block and Type":
             fill_value=0
         )
     
+    # Ensure the pivoted data is numeric for plotting
+    complaint_pivot = complaint_pivot.astype(float)
+
     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.