Join
Join a dataset with another dataset, by matching on one or more columns between the two tables.
If you pass a join_prefix, all column names in the join table will be named "{join_prefix}_{columnname}". If you don't pass a join_prefix, columns that share the same name in both tables will be only have the column from the base table included in the final output.
Name | Type | Description | Is Optional |
---|---|---|---|
join_table | table | Dataset object to join with the source dataset. | |
join_type | join_type | LEFT, RIGHT, or INNER | |
join_columns | join_dict | Columns to use for the join. Keys are columns in the source_table and values are on columns in the join_table. | |
join_prefix | value | Prefix all columns in the join_table with a string to differentiate them | True |
filters | filter_list | Filter logic on one or more columns. Can choose between a simple comparison filter or advanced filter using free text. | True |
internet_sales = rasgo.get.dataset(74)
product = rasgo.get.dataset(75)
ds2 = internet_sales.join(
join_table=product,
join_columns={'PRODUCTKEY':'PRODUCTKEY'},
join_type='LEFT',
join_prefix='product',
filters=['CUSTOMERKEY IS NOT NULL', 'ORDERDATE < CURRENT_DATE()'])
ds2.preview()
Last modified 1yr ago