polars.Expr.is_in

Expr.is_in(
    other: Expr | Collection[Any] | Series,
    *,
    nulls_equal: bool = False,
) → Expr

Check if elements of this expression are present in the other Series.

engine:In MemoryStreamingDistributed

Parameters:

other

Series or sequence of primitive type.

nulls_equalbool, default False

If True, treat null as a distinct value. Null values will not propagate.

Returns:

Expr

Expression of data type Boolean.

Examples

>>> df = pl.DataFrame(
...     {"sets": [[1, 2, 3], [1, 2], [9, 10]], "optional_members": [1, 2, 3]}
... )
>>> df.with_columns(contains=pl.col("optional_members").is_in("sets"))
shape: (3, 3)
┌───────────┬──────────────────┬──────────┐
│ sets      ┆ optional_members ┆ contains │
│ ---       ┆ ---              ┆ ---      │
│ list[i64] ┆ i64              ┆ bool     │
╞═══════════╪══════════════════╪══════════╡
│ [1, 2, 3] ┆ 1                ┆ true     │
│ [1, 2]    ┆ 2                ┆ true     │
│ [9, 10]   ┆ 3                ┆ false    │
└───────────┴──────────────────┴──────────┘