Not OP. But I'm guessing it's something like this: import pandas as pd def calculate_monthly_business_sum(df, date_column, value_column): """ Calcul

Not OP. But I'm guessing it's something like this: import pandas as pd def calculate_monthly_business_sum(df, date_column, value_column): """ Calculate monthly sums anchored to the last business day of each month Parameters: df: DataFrame with dates and values date_column: name of date column value_column: name of value column to sum Returns: DataFrame with sums anchored to last business day """ # Ensure date column is datetime df[date_column] = pd.to_datetime(df[date_column]) # Group by end of business month and sum monthly_sum = df.groupby(pd.Grouper( key=date_column, freq='BME' # Business Month End frequency ))[value_column].sum().reset_index() return monthly_sum # Example usage: df = pd.DataFrame({ 'date': ['2024-01-01', '2024-01-31', '2024-02-29'], 'amount': [100, 200, 300] }) result = calculate_monthly_business_sum(df, 'date', 'amount') print(result) Which you can run here => https://python-fiddle.com/examples/pandas?checkpoint=1732114144 https://python-fiddle.com/examples/pandas?checkpoint=1732114...