Updated lines 222-240 with: # Aggregate the data to count the number of visits to each State_2D visitation_counts = df['State_2D'].value_counts().reset_index() visitation_counts.columns = ['State_2D', 'Visitation_Count'] # Assuming State_2D is a 2D coordinate (e.g., 'x,y'), split it into separate columns visitation_counts[['x', 'y']] = visitation_counts['State_2D'].str.split(',', expand=True).astype(int) # Create the Plotly heatmap fig = px.density_heatmap(visitation_counts, x='x', y='y', z='Visitation_Count', title='Goal Position Visitation Counts Heatmap', labels={'x': 'X Coordinate', 'y': 'Y Coordinate', 'Visitation_Count': 'Visitation Count'}) # Display the heatmap using Streamlit st.title('Goal Position Visitation Counts Heatmap Visualization') st.plotly_chart(fig) df = pd.read_csv('intrinsic_analysis.csv') st.write("Intrinsic Analysis DataFrame:") st.dataframe(df)

app.py

@@ -217,4 +217,24 @@ fig = px.bar(visitation_counts, x='State_2D', y='Visitation_Count',
 
 # Display the plot using Streamlit
 st.title('Goal Position Visitation Counts Visualization')
-st.plotly_chart(fig)
+st.plotly_chart(fig)
+
+# Aggregate the data to count the number of visits to each State_2D
+visitation_counts = df['State_2D'].value_counts().reset_index()
+visitation_counts.columns = ['State_2D', 'Visitation_Count']
+
+# Assuming State_2D is a 2D coordinate (e.g., 'x,y'), split it into separate columns
+visitation_counts[['x', 'y']] = visitation_counts['State_2D'].str.split(',', expand=True).astype(int)
+
+# Create the Plotly heatmap
+fig = px.density_heatmap(visitation_counts, x='x', y='y', z='Visitation_Count', 
+                         title='Goal Position Visitation Counts Heatmap',
+                         labels={'x': 'X Coordinate', 'y': 'Y Coordinate', 'Visitation_Count': 'Visitation Count'})
+
+# Display the heatmap using Streamlit
+st.title('Goal Position Visitation Counts Heatmap Visualization')
+st.plotly_chart(fig)
+
+df = pd.read_csv('intrinsic_analysis.csv')
+st.write("Intrinsic Analysis DataFrame:")
+st.dataframe(df)