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Hierarchy.isin(*members: ScalarConstantT_co) → MembershipCondition[TypeAliasForwardRef, ‘IN’, TypeVar] | RelationalCondition[TypeAliasForwardRef, ‘EQ’, TypeVar]

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Hierarchy.isin(*member_paths: tuple[ScalarConstantT_co, …]) → HierarchyMembershipCondition[‘IN’, TypeVar]

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.

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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'