Update app.py

app.py

@@ -265,11 +265,9 @@ predicted_target = knn_predict(filtered_data, 'Predicted_target', ['latitude', '
 
 # Check if there are predictions to display
 if 'Predicted_target' in filtered_data.columns and not np.all(predicted_target == 0):
-    # Add predicted Predicted_target values to filtered_data
-    filtered_data['target_column'] = bound_data
 
-    # Apply bootstrap on the predicted values
-    lower_bound, higher_bound = bootstrap_stats(bound_data)
+    # Apply bootstrap - bounds
+    lower_bound, higher_bound = bootstrap_stats(filtered_data['target_column'])
 
     mean_value = np.mean(filtered_data['Predicted_target'])