Timeseries Agg

Date-based; Calculates a rolling aggregate based on a relative datetime window.

Pass in a date column, date_part and offsets to create look-back or look-forward windows.

Example use case: Aggregate all sales for a product with order dates within 2 months of this current order.

Parameters

Name	Type	Description	Is Optional
aggregations	agg_dict	Dictionary of columns and aggregate functions to apply. A column can have a list of multiple aggregates applied. One column will be created for each column:aggregate pair.
date	column	Column used to calculate the time window for aggregation
offsets	int_list	List of numeric values to offset the date column Positive values apply a look-back window. Negative values apply a look-forward window. One column will be created for each offset value.
date_part	date_part	Valid SQL date part to describe the grain of the date_offset
group_by	column_list	Column(s) to group by when calculating the agg window	True

Example

internet_sales = rasgo.get.dataset(74)

ds = internet_sales.timeseries_agg(
        aggregations={
          "SALESAMOUNT": ['SUM', 'MIN', 'MAX']
        },
        group_by=['PRODUCTKEY'],
        date='ORDERDATE',
        offsets=[-7, -14, 7, 14],
        date_part='MONTH'
       )

Source Code

RasgoTransforms/rasgotransforms/rasgotransforms/transforms/timeseries_agg/snowflake/timeseries_agg.sql at main · rasgointelligence/RasgoTransformsGitHub