Loading forecast_app/app.py +2 −2 Original line number Diff line number Diff line Loading @@ -209,7 +209,7 @@ def calculate_results(predictions, test_data): actual_values = watch_df['actual_demand'].tolist() predicted_values = watch_df['predicted_demand'].tolist() watch_performance[watch_id] = { watch_performance[int(watch_id)] = { # Convert numpy.int64 to Python int 'watch_name': watch_df['watch_name'].iloc[0], 'total_predicted': int(watch_df['predicted_demand'].sum()), 'total_actual': int(watch_df['actual_demand'].sum()), Loading Loading @@ -241,7 +241,7 @@ def calculate_results(predictions, test_data): # Build monthly comparison structure for templates monthly_comparison = [] for month in df['month'].unique(): for month in sorted(df['month'].unique()): # Sort months month_df = df[df['month'] == month] watches_list = [] Loading Loading
forecast_app/app.py +2 −2 Original line number Diff line number Diff line Loading @@ -209,7 +209,7 @@ def calculate_results(predictions, test_data): actual_values = watch_df['actual_demand'].tolist() predicted_values = watch_df['predicted_demand'].tolist() watch_performance[watch_id] = { watch_performance[int(watch_id)] = { # Convert numpy.int64 to Python int 'watch_name': watch_df['watch_name'].iloc[0], 'total_predicted': int(watch_df['predicted_demand'].sum()), 'total_actual': int(watch_df['actual_demand'].sum()), Loading Loading @@ -241,7 +241,7 @@ def calculate_results(predictions, test_data): # Build monthly comparison structure for templates monthly_comparison = [] for month in df['month'].unique(): for month in sorted(df['month'].unique()): # Sort months month_df = df[df['month'] == month] watches_list = [] Loading