❖ CarryOverColumns

❖ SDV Enterprise bundle. This feature is available for purchase as an SDV Enterprise bundle. For more information, visit our page to Explore SDV.

Use the CarryOverColumns CAG Pattern when you have the same columns in different tables, and the values of those columns have to match up according to a key (ID) column.

The 'Type' column is carried over based on the ID/Account ID information.

Pattern API

This functionality is in Beta. At this time, select SDV Enterprise users have been invited to use this feature.

Create a CarryOverColumns pattern object

Parameters:

• (required) common_column_info: A list of dictionaries that describe all the columns within your dataset that are carried over. Each dictionary should have the following keys:

  • table_name: The name of the table that contains the column

  • carryover_column_name: The name of the column that is repeated across your dataset

  • key_column_name: The name of the column to use as the key for the carried over column. Must be a PII or ID sdtype.

Please supply 2 or more columns for this CAG pattern.

from sdv.cag import CarryOverColumns

my_pattern = CarryOverColumns(
    common_column_info=[{
        'table_name': 'Account',
        'carryover_column_name': 'Type',
        'key_column_name': 'ID'
    }, {
        'table_name': 'Transaction',
        'carryover_column_name': 'Type',
        'key_column_name': 'Account ID'
    }]
)

Make sure that all the tables and columns in you provide are in your Metadata.

Usage

Apply the pattern to any SDV synthesizer. Then fit and sample as usual.

synthesizer = HSASynthesizer(metadata)
synthesizer.add_cag(patterns=[my_pattern])

synthesizer.fit(data)
synthetic_data = synthesizer.sample()