New changes

app.py

@@ -2,6 +2,9 @@ import pandas as pd
 import streamlit as st
 import altair as alt
 
+alt.themes.enable('default')  # Use Altair's default responsive theme
+
+
 # Load and clean dataset
 url = "https://raw.githubusercontent.com/UIUC-iSchool-DataViz/is445_data/main/building_inventory.csv"
 df = pd.read_csv(url, na_values={'Year Acquired': 0, 'Year Constructed': 0, 'Square Footage': 0})
@@ -64,7 +67,7 @@ stacked_bar_chart_county = alt.Chart(county_agency_building).mark_bar().encode(
 )
 
 # Display the stacked bar chart in Streamlit
-st.altair_chart(stacked_bar_chart_county)
+st.altair_chart(stacked_bar_chart_county,use_container_width=True)
 
 # Write-up for Stacked Bar Chart
 
@@ -90,6 +93,7 @@ If I had more time, I would focus on adding **interactivity** by implementing fi
 st.markdown("""
     <h2 style="width: 800px;">Visualization 2: County, Total Floors, and Square Footage</h2>
 """, unsafe_allow_html=True)
+
 bubble_chart = alt.Chart(df).mark_circle().encode(
     x=alt.X('County:N', title='County'),
     y=alt.Y('sum(Square Footage):Q', title='Total Square Footage (sq ft)'),
@@ -102,7 +106,7 @@ bubble_chart = alt.Chart(df).mark_circle().encode(
     title="Relationship Between County, Square Footage, and Total Floors"
 )
 
-st.altair_chart(bubble_chart)
+st.altair_chart(bubble_chart,use_container_width=True)
 
 
 # Write-up for Bubble Chart
@@ -139,7 +143,7 @@ heatmap = alt.Chart(df).mark_rect().encode(
     title="Heatmap of Building Count by County and Status"
 )
 
-st.altair_chart(heatmap)
+st.altair_chart(heatmap, use_container_width=True)