Filter & Label Utils

Filter ibis table rows by arbitrary boolean conditions and tag the matches.

filter_and_label_by_condition(table, conditions, label_col='label')

Filter rows matching any condition and tag each kept row with its matching label.

A row is kept if it matches at least one condition; the label is the first matching key in the dict order of conditions.

Parameters:

Name	Type	Description	Default
table	Table	The ibis table to filter.	required
conditions	dict[str, BooleanColumn]	Labels mapped to boolean row conditions.	required
label_col	str	Name of the label column to add. Defaults to "label".	'label'

Returns:

Type	Description
Table	ibis.Table: Filtered table with the label column added.

Source code in openretailscience/utils/filter_and_label.py

def filter_and_label_by_condition(
    table: ibis.Table,
    conditions: dict[str, ibis.expr.types.BooleanColumn],
    label_col: str = "label",
) -> ibis.Table:
    """Filter rows matching any condition and tag each kept row with its matching label.

    A row is kept if it matches at least one condition; the label is the first matching
    key in the dict order of ``conditions``.

    Args:
        table (ibis.Table): The ibis table to filter.
        conditions (dict[str, ibis.expr.types.BooleanColumn]): Labels mapped to boolean
            row conditions.
        label_col (str): Name of the label column to add. Defaults to ``"label"``.

    Returns:
        ibis.Table: Filtered table with the label column added.
    """
    branches = [(condition, ibis.literal(label)) for label, condition in conditions.items()]
    combined_condition = ibis.or_(*[condition for condition, _ in branches])

    return table.filter(combined_condition).mutate(**{label_col: ibis.cases(*branches)})