> ## Documentation Index
> Fetch the complete documentation index at: https://docs.activeviam.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Level.isin()

<span id="atoti.Level.isin" />

> Level.isin(<br />
>     *\*members*: ScalarConstantT\_co,<br />
> ) → MembershipCondition\[TypeAliasForwardRef, 'IN', TypeVar] | RelationalCondition\[TypeAliasForwardRef, 'EQ', TypeVar]

Return a condition evaluating to `True` where this level’s current member is included in the given *members*, and evaluating to `False` elsewhere.

### Parameters

<h4 id="atoti.Level.isin.members">
  *\*members*
</h4>

One or more values that the level members will be compared against.

***

```pycon theme={"languages":{"custom":["/engine/python-sdk/0.9/languages/pycon.tmLanguage.json"]}}
>>> df = pd.DataFrame(
...     columns=["City", "Price"],
...     data=[
...         ("Berlin", 150.0),
...         ("London", 240.0),
...         ("New York", 270.0),
...         ("Paris", 200.0),
...     ],
... )
>>> table = session.read_pandas(df, keys={"City"}, table_name="Example")
>>> cube = session.create_cube(table)
>>> l, m = cube.levels, cube.measures
>>> m["Price.SUM in London and Paris"] = tt.filter(
...     m["Price.SUM"], l["City"].isin("London", "Paris")
... )
>>> cube.query(
...     m["Price.SUM"],
...     m["Price.SUM in London and Paris"],
...     levels=[l["City"]],
... )
         Price.SUM Price.SUM in London and Paris
City
Berlin      150.00
London      240.00                        240.00
New York    270.00
Paris       200.00                        200.00
```