Final Commit

app.py

@@ -2,8 +2,9 @@ import pandas as pd
 import streamlit as st
 import altair as alt
 
-st.set_page_config(page_title="Building Inventory Analysis", layout="wide")
+
 import streamlit.components.v1 as components
+st.set_page_config(page_title="Building Inventory Analysis", layout="wide")
 
 components.html(
     """
@@ -11,7 +12,7 @@ components.html(
     document.querySelector('iframe').style.height = '100vh';
     </script>
     """,
-    height=0,  # Prevents extra space for the component
+    height=0,  
 )
 
 
@@ -28,17 +29,13 @@ st.markdown(
 )
 
 
-
-
 # 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")
-
 
 
 # Displaying the Dataset Overview
-st.header("Dataset Overview")
+st.header("Building Inventory Dataset Analysis")
 st.write("Below are the first 10 rows of the dataset:")
 st.write(df.head(10))
 st.write(f"The shape of dataset before cleaning is: {df.shape}")
@@ -60,9 +57,9 @@ df = df.dropna(subset=['Year Acquired', 'Year Constructed'])
 df['County'] = df['County'].fillna('Unknown')
 df['Square Footage'] = df['Square Footage'].fillna(df['Square Footage'].mean())
 
-# st.subheader("Missing Values After Cleaning")
-# st.write(df.isnull().sum())
-# st.write(f"The shape of dataset after cleaning is: {df.shape}")
+st.subheader("Missing Values After Cleaning")
+st.write(df.isnull().sum())
+st.write(f"The shape of dataset after cleaning is: {df.shape}")
 
 
 # Visualization 1:  Number of Buildings by County and Agency