Update app.py

app.py

@@ -3,7 +3,6 @@ import folium
 from folium.plugins import MarkerCluster, HeatMap
 import pandas as pd
 import plotly.express as px
-from plotly.subplots import make_subplots
 
 # Function to create the map
 @st.cache_data
@@ -45,15 +44,20 @@ def create_map(df, selected_year, selected_severity=None):
     return m
 
 # Function to create a bar chart based on accident severity
-def create_bar_chart(df, selected_year, selected_severity=None):
+def create_bar_chart(df, selected_year):
     filtered_df = df[df['Year'] == selected_year]
-    if selected_severity:
-        filtered_df = filtered_df[filtered_df['Injuryseverity'] == selected_severity]
-    
     severity_count = filtered_df['Injuryseverity'].value_counts().reset_index()
     severity_count.columns = ['Injuryseverity', 'Count']
     
-    fig = px.bar(severity_count, x='Injuryseverity', y='Count', title="Accidents by Severity")
+    fig = px.bar(
+        severity_count, 
+        x='Injuryseverity', 
+        y='Count', 
+        title="Accidents by Severity",
+        labels={'Injuryseverity': 'Severity', 'Count': 'Number of Accidents'}
+    )
+    fig.update_traces(marker_color='blue')
+    fig.update_layout(clickmode='event+select')  # Enable interactivity
     return fig
 
 # Streamlit app
@@ -64,17 +68,29 @@ def app():
     # Sidebar for selection
     st.sidebar.header("Select Filters")
     selected_year = st.sidebar.selectbox("Select Year", df['Year'].unique())
-    selected_severity = st.sidebar.selectbox("Select Severity", df['Injuryseverity'].unique())
-
+    
+    # Initialize session state for selected severity
+    if "selected_severity" not in st.session_state:
+        st.session_state["selected_severity"] = None
+    
+    # Bar Chart visualization
+    st.subheader("Accidents by Severity")
+    bar_chart = create_bar_chart(df, selected_year)
+    selected_points = st.plotly_chart(bar_chart)
+    
+    # Update severity based on bar chart selection
+    if selected_points:
+        selected_data = selected_points['points'][0]['x']  # Get the clicked bar's x value
+        st.session_state["selected_severity"] = selected_data
+    
     # Map visualization
     st.subheader("Accidents Map")
+    selected_severity = st.session_state["selected_severity"]
     map_obj = create_map(df, selected_year, selected_severity)
     st.components.v1.html(map_obj._repr_html_(), height=600)
     
-    # Bar Chart visualization
-    st.subheader("Accidents by Severity")
-    bar_chart = create_bar_chart(df, selected_year, selected_severity)
-    st.plotly_chart(bar_chart)
+    # Display current filter
+    st.sidebar.write(f"Selected Severity: {selected_severity if selected_severity else 'All'}")
 
 # Run the Streamlit app
 if __name__ == "__main__":