atoti.Hierarchy.isin()#

Hierarchy.isin(*members: ScalarT_co) → RelationalCondition[TypeAliasForwardRef, Literal['EQ'], +ScalarT_co]#
Hierarchy.isin(*member_paths: tuple[ScalarT_co, ...]) → HierarchyIsInCondition[Literal['IS_IN'], +ScalarT_co]

Return a condition evaluating to True where this hierarchy’s current member (or its path) is included in the given members (or member_paths), and evaluating to False elsewhere.

Parameters:

members_or_member_paths –

Either:

  • One or more members. In that case, all the hierarchy’s members are expected to be unique across all the levels of the hierarchy.

  • One or more member paths expressed as tuples of members starting from the top of the hierarchy.

Example

>>> df = pd.DataFrame(
...     columns=["Country", "City", "Price"],
...     data=[
...         ("Germany", "Berlin", 150.0),
...         ("Germany", "Hamburg", 120.0),
...         ("United Kingdom", "Bath", 240.0),
...         ("United Kingdom", "London", 270.0),
...     ],
... )
>>> table = session.read_pandas(
...     df, keys={"Country", "City"}, table_name="Example"
... )
>>> cube = session.create_cube(table, mode="manual")
>>> h = cube.hierarchies
>>> h["Geography"] = [table["Country"], table["City"]]

Condition on members:

>>> h["Geography"].isin("Germany", "London")
h['Example', 'Geography'].isin('Germany', 'London')

Condition on member paths:

>>> h["Geography"].isin(("Germany",), ("United Kingdom", "Bath"))
h['Example', 'Geography'].isin(('Germany',), ('United Kingdom', 'Bath'))

Members and member paths cannot be mixed:

>>> h["Geography"].isin("Germany", ("United Kingdom", "Bath"))
Traceback (most recent call last):
    ...
ValueError: Expected either only members or only member paths but both were mixed: `('Germany', ('United Kingdom', 'Bath'))`.

Conditions on single members are normalized to equality conditions:

>>> h["Geography"].isin("Germany")
h['Example', 'Geography'] == 'Germany'