Update app.py

app.py

@@ -78,12 +78,15 @@ total_rides_graph = df_total_rides.hvplot.bar(x='Days', y='Rides', color='black'
 # Your original data processing
 weekly_data = weekly_data.groupby(['Day', 'Time']).mean('Rides')
 weekly_data1 = weekly_data.unstack(level=0)
+average_rides = weekly_data1.T.mean()
 
-# Create a Panel object
-avg_rides_graph = pn.panel(weekly_data1.T.mean().hvplot(c='black', xlabel='Date', ylabel='Average rides',
-                                                        xticks=10, title='Average Uber rides on any day in July 2014 at NYC',
-                                                        height=400, width=800))
+# Create a HoloViews plot
+rides_plot = average_rides.hvplot(c='black', xlabel='Date', ylabel='Average rides',
+                                   xticks=10, title='Average Uber rides on any day in July 2014 at NYC',
+                                   height=400, width=800)
 
+# Wrap the plot in a Panel
+avg_rides_panel = pn.panel(rides_plot)
 # --- Code 5 ---
 # Countplot using hvplot
 BaseMapper = {'B02512': 'Unter', 'B02598': 'Hinter', 'B02617': 'Weiter', 'B02682': 'Schmecken', 'B02764': 'Danach-NY'}
@@ -159,7 +162,7 @@ def update_chart(event):
     elif event.new == 'Total Rides per Day':
         panel_layout[1] = total_rides_graph
     elif event.new == 'Avg Rides per Day':
-        panel_layout[1] = avg_rides_graph
+        panel_layout[1] = avg_rides_panel
     elif event.new == 'Top Rides City':
         panel_layout[1] = plot_top_rides_city
     elif event.new == 'Predicting Distance':