Update app.py

app.py

@@ -30,13 +30,12 @@ county_count.columns = ['County', 'Building Count']
 
 county_chart = alt.Chart(county_count).mark_bar(color='teal').encode(
     alt.X('Building Count:Q', title='Number of Buildings'),
-    alt.Y('County:N', sort='-x', title='County'),
-    tooltip=['County', 'Building Count']
+    alt.Y('County:N', sort='-x', title='County')
 ).properties(
     width=700,
     height=400,
     title='Number of Buildings per County'
-).interactive()
+)
 
 st.altair_chart(county_chart, use_container_width=True)
 
@@ -47,17 +46,13 @@ This bar chart illustrates the number of buildings in each county, highlighting
   - A horizontal bar chart is used to accommodate long county names and facilitate easy comparison.
   - Counties are sorted in descending order based on building count to emphasize those with the most buildings.
   - The teal color provides a calm and professional appearance.
-  - Interactive tooltips offer precise counts upon hovering.
 - **Potential Improvements**:
   - Incorporate filters to allow users to focus on specific regions or agencies.
   - Add a map visualization to provide spatial context to the data.
 """)
 
 # Visualization 2: Year-wise Construction of Buildings
-# Data Preprocessing for Year-wise Construction Visualization
-# Convert 'Year Constructed' to numeric, handling errors
-data['Year Constructed'] = pd.to_numeric(data['Year Constructed'], errors='coerce')
-
+st.header("2. Year-wise Construction of Buildings")
 # Filter out rows where 'Year Constructed' is 0 or NaN
 data_filtered = data[(data['Year Constructed'] > 0) & (~data['Year Constructed'].isna())]
 
@@ -66,17 +61,14 @@ yearly_construction = data_filtered['Year Constructed'].value_counts().reset_ind
 yearly_construction.columns = ['Year Constructed', 'Building Count']
 yearly_construction = yearly_construction.sort_values('Year Constructed')
 
-# Visualization: Year-wise Construction of Buildings
-st.header("2. Year-wise Construction of Buildings")
 year_chart = alt.Chart(yearly_construction).mark_line(point=True, color='orange').encode(
     alt.X('Year Constructed:Q', title='Year Constructed'),
-    alt.Y('Building Count:Q', title='Number of Buildings'),
-    tooltip=['Year Constructed', 'Building Count']
+    alt.Y('Building Count:Q', title='Number of Buildings')
 ).properties(
     width=700,
     height=400,
     title='Number of Buildings Constructed Over Time'
-).interactive()
+)
 
 st.altair_chart(year_chart, use_container_width=True)
 
@@ -87,13 +79,11 @@ This line chart displays the number of buildings constructed each year, revealin
   - A line chart effectively shows changes over time and highlights trends.
   - Data points are marked to emphasize individual years.
   - The orange color draws attention to the trend line.
-  - Interactive tooltips provide exact counts for each year.
 - **Potential Improvements**:
   - Implement a rolling average to smooth out year-to-year fluctuations.
   - Allow users to filter the data by building type or agency to explore specific trends.
 """)
 
-
 # Footer
 st.markdown("""
 ---