polars.Expr.map_batches

Expr.map_batches(

function: Callable[[Series], Series | Any],

return_dtype: PolarsDataType | None = None,

*,

agg_list: bool = False,

) → Self

Apply a custom python function to a whole Series or sequence of Series.

The output of this custom function must be a Series. If you want to apply a custom function elementwise over single values, see map_elements(). A reasonable use case for map functions is transforming the values represented by an expression using a third-party library.

Read more in the book.

Parameters:

function

Lambda/function to apply.

return_dtype

Dtype of the output Series.

agg_list

Aggregate list.

Warning

If return_dtype is not provided, this may lead to unexpected results. We allow this, but it is considered a bug in the user’s query.

See also

map_elements

replace

Notes

If you are looking to map a function over a window function or group_by context, refer to func:map_elements instead.

Examples

>>> df = pl.DataFrame(
...     {
...         "sine": [0.0, 1.0, 0.0, -1.0],
...         "cosine": [1.0, 0.0, -1.0, 0.0],
...     }
... )
>>> df.select(pl.all().map_batches(lambda x: x.to_numpy().argmax()))
shape: (1, 2)
┌──────┬────────┐
│ sine ┆ cosine │
│ ---  ┆ ---    │
│ i64  ┆ i64    │
╞══════╪════════╡
│ 1    ┆ 0      │
└──────┴────────┘