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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

Last modified 1yr ago