app.py

import streamlit as st
import pandas as pd
import altair as alt


url = 'https://raw.githubusercontent.com/UIUC-iSchool-DataViz/is445_data/main/building_inventory.csv'
data = pd.read_csv(url)

# Visualization 1: Building Status Distribution
status_chart = alt.Chart(data).mark_bar().encode(
    x=alt.X('Bldg Status:N', title='Building Status'),
    y=alt.Y('count():Q', title='Number of Buildings'),
    color='Bldg Status:N'
).properties(
    title="Distribution of Building Status"
)

st.altair_chart(status_chart, use_container_width=True)
st.write("### Visualization 1: Distribution of Building Status")
st.write("""
This bar chart illustrates the distribution of building statuses across categories such as "In Use," "Abandon," and "In Progress." 
By assigning unique colors to each category, the chart makes it easy to distinguish between statuses and quickly identify the most 
common one. The "In Use" status, highlighted in a bold color, stands out as the dominant category, indicating a high number of active 
buildings. This straightforward layout enables a quick overview of building statuses, and with additional time, interactivity like 
tooltips or filtering by specific statuses could provide further insights.
""")
# Visualization 2: Primary Usage by Building Status ("In Use")

# Filter data to only include buildings with 'Bldg Status' equal to "In Use"
in_use_data = data[data['Bldg Status'] == "In Use"]

filtered_chart = alt.Chart(in_use_data).mark_bar().encode(
    x=alt.X('Usage Description:N', title='Primary Usage Type'),
    y=alt.Y('count():Q', title='Number of Buildings'),
    color=alt.Color('Usage Description:N', title='Primary Usage Type')
).properties(
    title="Distribution of Primary Usage Type for Buildings In Use",
    width=300
).configure_axis(
    labelAngle=45
)

st.altair_chart(filtered_chart, use_container_width=True)
st.write("### Visualization 2: Distribution of Primary Usage Type for Buildings In Use")
st.write("""
This bar chart focuses on the primary usage types for buildings marked as "In Use," revealing the functional distribution of active buildings. 
Each usage type, such as "Assembly," "Industrial," and "Storage," is represented by a different color, making it visually accessible and easy 
to compare categories. Rotated labels on the x-axis improve readability for longer usage descriptions, and the chart's filtered focus on active 
buildings allows for a targeted analysis of their purposes. If time permitted, adding interactivity, such as tooltips with precise counts or 
comparisons across additional statuses, would enhance the depth of insights provided.
""")