Update app.py

app.py

@@ -1,6 +1,7 @@
 import streamlit as st
 import pandas as pd
 import plotly.express as px
+import altair as alt
 import folium
 from folium.plugins import HeatMap, MarkerCluster
 from streamlit_folium import st_folium
@@ -128,6 +129,120 @@ def create_map(df, selected_year):
     
     return m
 
+def 5_create_injuries_fatalities_chart(crash_data):
+
+    # 5th visualization title
+    st.header("5. Total Injuries and Fatalities by Month")
+    
+    # Filter rows where we have valid data for all necessary columns
+    crash_data = crash_data[['DateTime', 'Totalinjuries', 'Totalfatalities', 'Unittype_One', 'Unittype_Two']].dropna()
+
+    # Convert "DateTime" to datetime type
+    crash_data['DateTime'] = pd.to_datetime(crash_data['DateTime'], errors='coerce')
+    crash_data['Month'] = crash_data['DateTime'].dt.month_name()
+
+    # sort months in order
+    month_order = ['January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December']
+    crash_data['Month'] = pd.Categorical(crash_data['Month'], categories=month_order, ordered=True)
+
+    # Dropdown for Unit Type selection
+    # Dropdown for Unit Type selection
+    # st.sidebar.selectbox("Select Unit Type", options=['Total'] + crash_data['Unittype_One'].dropna().unique().tolist())  # previous location of dropdown in sidebar
+    # unit_type = st.selectbox("Select Unit Type", options=['Total'] + crash_data['Unittype_One'].dropna().unique().tolist())
+    unit_type_pairs = set()
+    for _, row in crash_data[['Unittype_One', 'Unittype_Two']].dropna().iterrows():
+        if row['Unittype_One'] != 'Driverless' or row['Unittype_Two'] != 'Driverless':
+            pair = ' vs '.join(sorted([row['Unittype_One'], row['Unittype_Two']]))
+            unit_type_pairs.add(pair)
+    # unit_type_pairs = list(unit_type_pairs) # modified as below to sort the dropdown options in alphabetical order
+    unit_type_pairs = sorted(list(unit_type_pairs))
+    unit_type = st.selectbox("Select Unit Type Pair", options=['Total'] + unit_type_pairs)
+
+    # Filter data based on the selected unit type
+    if unit_type == 'Total':
+        filtered_data = crash_data
+    else:
+        unit_one, unit_two = unit_type.split(' vs ')
+        filtered_data = crash_data[((crash_data['Unittype_One'] == unit_one) & (crash_data['Unittype_Two'] == unit_two)) |
+                                   ((crash_data['Unittype_One'] == unit_two) & (crash_data['Unittype_Two'] == unit_one))]
+
+    # Group data by month and calculate total injuries and fatalities
+    monthly_sum = filtered_data.groupby('Month').agg({'Totalinjuries': 'sum', 'Totalfatalities': 'sum'}).reset_index()
+
+    # Reshape the data for easier plotting
+    injuries = monthly_sum[['Month', 'Totalinjuries']].rename(columns={'Totalinjuries': 'Value'})
+    injuries['Measure'] = 'Total Injuries'
+
+    fatalities = monthly_sum[['Month', 'Totalfatalities']].rename(columns={'Totalfatalities': 'Value'})
+    fatalities['Measure'] = 'Total Fatalities'
+
+    combined_data = pd.concat([injuries, fatalities])
+
+    # Originally tried to use bar chart but switched to line chart for better trend visualization
+    # alt.Chart(monthly_sum).mark_bar().encode(
+    #     x=alt.X('Month', sort=month_order, title='Month'),
+    #     y=alt.Y('Totalinjuries', title='Total Injuries', axis=alt.Axis(titleColor='blue', labelColor='blue', tickColor='blue')),
+    #     color=alt.value('blue'),
+    #     tooltip=['Month', 'Totalinjuries']
+    # ).properties(
+    #     title='Total Injuries and Fatalities by Month',
+    #     width=300,
+    #     height=300
+    # ) + alt.Chart(monthly_sum).mark_bar().encode(
+    #     x=alt.X('Month', sort=month_order, title='Month'),
+    #     y=alt.Y('Totalfatalities', title='Total Fatalities', axis=alt.Axis(titleColor='red', labelColor='red', tickColor='red')),
+    #     color=alt.value('red'),
+    #     tooltip=['Month', 'Totalfatalities']
+    # )
+
+    # Tried to figure out how to plot a legend using altair
+    # line_chart = alt.Chart(monthly_sum).mark_line(point=True).encode(
+    #     x=alt.X('Month', sort=month_order, title='Month'),
+    #     y=alt.Y('Totalinjuries', title='Total Injuries & Fatalities', axis=alt.Axis(titleColor='black')),
+    #     color=alt.value('blue'),
+    #     tooltip=['Month', 'Totalinjuries']
+    # ).properties(
+    #     title=f'Total Injuries and Fatalities by Month for Unit Type Pair: {unit_type}',
+    #     width=600,
+    #     height=400
+    # ) + alt.Chart(monthly_sum).mark_line(point=True).encode(
+    #     x=alt.X('Month', sort=month_order, title='Month'),
+    #     y=alt.Y('Totalfatalities', axis=alt.Axis(titleColor='red')),
+    #     color=alt.value('red'),
+    #     tooltip=['Month', 'Totalfatalities']
+    # ).configure_legend(
+    #     titleFontSize=14,
+    #     labelFontSize=12,
+    #     titleColor='black',
+    #     labelColor='black'
+    # )
+    
+    # Plot line chart
+    line_chart = alt.Chart(combined_data).mark_line(point=True).encode(
+        x=alt.X('Month:N', sort=month_order, title='Month'),
+        y=alt.Y('Value:Q', title='Total Injuries & Fatalities'),
+        color=alt.Color('Measure:N', title='', scale=alt.Scale(domain=['Total Injuries', 'Total Fatalities'], range=['blue', 'red'])),
+        tooltip=['Month', 'Measure:N', 'Value:Q']
+    ).properties(
+        title=f'Total Injuries and Fatalities by Month for Unit Type Pair: {unit_type}',
+        width=600,
+        height=400
+    )
+
+    # # Combine the charts (trying to make legend)
+    # combined_chart = alt.layer(line_chart_injuries, line_chart_fatalities).properties(
+    #     title=f'Total Injuries and Fatalities by Month for Unit Type Pair: {unit_type}',
+    #     width=600,
+    #     height=400
+    # ).configure_legend(
+    #     titleFontSize=14,
+    #     labelFontSize=12,
+    #     titleColor='black',
+    #     labelColor='black'
+    # )
+    
+    return line_chart
+
 def main():
     st.title('Traffic Crash Analysis')
     
@@ -185,5 +300,11 @@ def main():
                 returned_objects=["null_drawing"]
             )
 
+    # Create 5th Visualization: Injuries and fatalities chart
+    injuries_fatalities_chart = 5_create_injuries_fatalities_chart(df)
+    st.altair_chart(injuries_fatalities_chart, use_container_width=True)
+    st.markdown("#### TODO: add write-up for this 5th chart.")
+
+
 if __name__ == "__main__":
     main()