Updated lines 209-220 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'] # Create the Plotly bar chart fig = px.bar(visitation_counts, x='State_2D', y='Visitation_Count', title='Goal Position Visitation Counts', labels={'State_2D': 'State 2D', 'Visitation_Count': 'Visitation Count'}) # Display the plot using Streamlit st.title('Goal Position Visitation Counts Visualization') st.plotly_chart(fig)

app.py

@@ -206,15 +206,14 @@ st.plotly_chart(fig_heatmap)
 # Load the CSV data
 df = pd.read_csv('goal_rows.csv')
 
-# Assuming the CSV has columns 'goal_position' and 'visitation_count'
-# If the column names are different, adjust the following lines accordingly
-goal_positions = df['goal_position']
-visitation_counts = df['visitation_count']
+# 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']
 
 # Create the Plotly bar chart
-fig = px.bar(df, x='goal_position', y='visitation_count', 
+fig = px.bar(visitation_counts, x='State_2D', y='Visitation_Count', 
              title='Goal Position Visitation Counts',
-             labels={'goal_position': 'Goal Position', 'visitation_count': 'Visitation Count'})
+             labels={'State_2D': 'State 2D', 'Visitation_Count': 'Visitation Count'})
 
 # Display the plot using Streamlit
 st.title('Goal Position Visitation Counts Visualization')