atoti.Measure.isin()

Measure.isin(*values: Constant) → IsInCondition[MeasureIdentifier, 'IS_IN', Constant] | RelationalCondition[MeasureIdentifier, 'EQ', Constant]

Measure.isin(*values: Constant | None) → IsInCondition[MeasureIdentifier, 'IS_IN', Constant | None] | RelationalCondition[MeasureIdentifier, 'EQ', Constant | None]

Return a condition evaluating to True where this measure evaluates to one of the given values, and evaluating to False elsewhere.

Parameters:

values – One or more values that the measure will be compared against.

Example

>>> df = pd.DataFrame(
...     columns=["City", "Price"],
...     data=[
...         ("Berlin", 150),
...         ("London", 270),
...         ("Madrid", 200),
...     ],
... )
>>> table = session.read_pandas(df, keys={"City"}, table_name="Example")
>>> cube = session.create_cube(table)
>>> m = cube.measures
>>> m["Price.SUM"].isin(150, 270)
m['Price.SUM'].isin(150, 270)

Conditions on single values are normalized to equality conditions:

>>> m["Price.SUM"].isin(150)
m['Price.SUM'] == 150