snowflake.snowpark.DataFrameAnalyticsFunctions.cumulative_agg¶
- DataFrameAnalyticsFunctions.cumulative_agg(aggs: ~typing.Dict[str, ~typing.List[str]], group_by: ~typing.List[str], order_by: ~typing.List[str], is_forward: bool, col_formatter: ~typing.Callable[[str, str], str] = <function DataFrameAnalyticsFunctions._default_col_formatter>) DataFrame [source]¶
Applies cummulative aggregations to the specified columns of the DataFrame using defined window direction, and grouping and ordering criteria.
- Parameters:
aggs – A dictionary where keys are column names and values are lists of the desired aggregation functions.
order_by – A list of column names that specify the order in which rows are processed.
group_by – A list of column names on which the DataFrame is partitioned for separate window calculations.
is_forward – A boolean indicating the direction of accumulation. True for ‘forward’ and False for ‘backward’.
col_formatter – An optional function for formatting output column names, defaulting to the format ‘<input_col>_<agg>’. This function takes two arguments: ‘input_col’ (str) for the column name, ‘operation’ (str) for the applied operation, and returns a formatted string for the column name.
- Returns:
A Snowflake DataFrame with additional columns corresponding to each specified cumulative aggregation.
- Raises:
ValueError – If an unsupported value is specified in arguments.
TypeError – If an unsupported type is specified in arguments.
SnowparkSQLException – If an unsupported aggregration is specified.
Example
>>> sample_data = [ ... ["2023-01-01", 101, 200], ... ["2023-01-02", 101, 100], ... ["2023-01-03", 101, 300], ... ["2023-01-04", 102, 250], ... ] >>> df = session.create_dataframe(sample_data).to_df( ... "ORDERDATE", "PRODUCTKEY", "SALESAMOUNT" ... ) >>> res = df.analytics.cumulative_agg( ... aggs={"SALESAMOUNT": ["SUM", "MIN", "MAX"]}, ... group_by=["PRODUCTKEY"], ... order_by=["ORDERDATE"], ... is_forward=True ... ) >>> res.show() ---------------------------------------------------------------------------------------------------------- |"ORDERDATE" |"PRODUCTKEY" |"SALESAMOUNT" |"SALESAMOUNT_SUM" |"SALESAMOUNT_MIN" |"SALESAMOUNT_MAX" | ---------------------------------------------------------------------------------------------------------- |2023-01-03 |101 |300 |300 |300 |300 | |2023-01-02 |101 |100 |400 |100 |300 | |2023-01-01 |101 |200 |600 |100 |300 | |2023-01-04 |102 |250 |250 |250 |250 | ----------------------------------------------------------------------------------------------------------