Changes

app.py

@@ -2,11 +2,13 @@ import pandas as pd
 import streamlit as st
 import altair as alt
 
+st.title("Building Inventory Analysis")
+
 # 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})
 # st.set_page_config(page_title="Building Inventory Analysis", layout="wide")
-st.title("Building Inventory Analysis")
+
 
 
 # Displaying the Dataset Overview
@@ -46,20 +48,34 @@ st.markdown("""
 # Group the data by 'County' and 'Agency Name' to get the count of buildings
 county_agency_building = df.groupby(['County', 'Agency Name']).size().reset_index(name='Number of Buildings')
 
+
+
 # Create a stacked bar chart with adjusted legend properties
-stacked_bar_chart_county = alt.Chart(county_agency_building).mark_bar().encode(
-    x=alt.X('County:N', title='County', sort='-y'),
-    y=alt.Y('Number of Buildings:Q', title='Number of Buildings'),
-    color=alt.Color('Agency Name:N', title='Agency Name', legend=alt.Legend(orient='top', padding=10, symbolSize=150)),
-    tooltip=['County', 'Agency Name', 'Number of Buildings']
-).properties(
-    width=800,
-    height=500,
-    title="Stacked Bar Graph for Number of Buildings by County and Agency"
-)
+stacked_bar_chart_county = (
+    alt.Chart(county_agency_building)
+    .mark_bar()
+    .encode(
+        alt.X('County:N', title='County', sort='-y'),
+        alt.Y(
+            'Number of Buildings:Q', 
+            title='Number of Buildings',
+            scale=alt.Scale(domain=[0, 550]),
+            ),
+        color = 
+            alt.Color(
+                'Agency Name:N', 
+                title='Agency Name', 
+                legend=alt.Legend(orient='right', padding=0, symbolSize=50,labelFontSize=10,labelOverlap="greedy", columnPadding=0,rowPadding=0)
+                ),
+        tooltip=['County', 'Agency Name', 'Number of Buildings']
+        ).properties(
+        width=800,
+        height=500,
+        title="Stacked Bar Graph for Number of Buildings by County and Agency"
+))
 
 # Display the stacked bar chart in Streamlit
-st.altair_chart(stacked_bar_chart_county,use_container_width=True)
+st.altair_chart(stacked_bar_chart_county,theme="streamlit", use_container_width=True)
 
 # Write-up for Stacked Bar Chart
 
@@ -98,7 +114,7 @@ bubble_chart = alt.Chart(df).mark_circle().encode(
     title="Relationship Between County, Square Footage, and Total Floors"
 ).interactive()
 
-st.altair_chart(bubble_chart,use_container_width=True)
+st.altair_chart(bubble_chart,theme="streamlit", use_container_width=True)
 
 
 # Write-up for Bubble Chart
@@ -135,7 +151,7 @@ heatmap = alt.Chart(df).mark_rect().encode(
     title="Heatmap of Building Count by County and Status"
 )
 
-st.altair_chart(heatmap, use_container_width=True)
+st.altair_chart(heatmap, theme="streamlit", use_container_width=True)
 
 
 
@@ -162,20 +178,3 @@ st.markdown("""
     **~By Janhavi Tushar Zarapkar**
 """, unsafe_allow_html=True)
 
-
-st.markdown("<h4 style='text-decoration: underline;'>Visualization 2</h4>", unsafe_allow_html=True)
-county_agency_data = df.dropna(subset=['County', 'Agency Name'])
-county_agency_count = county_agency_data.groupby('County')['Agency Name'].nunique().reset_index()
-county_agency_count.rename(columns={'Agency Name': 'Unique Agencies'}, inplace=True)
-
-county_agency_chart = alt.Chart(county_agency_count).mark_bar().encode(
-    x=alt.X('County:N', sort='-y', title="County"),
-    y=alt.Y('Unique Agencies:Q', title="Number of Agencies"),
-    color=alt.Color('Unique Agencies:Q', scale=alt.Scale(scheme='viridis')),
-    tooltip=['County:N', 'Unique Agencies:Q']
-).properties(
-    width=700,
-    height=400,
-    title="Unique Agencies in Each County"
-)
-st.altair_chart(county_agency_chart, use_container_width=True)