polars.Expr.apply#

Expr.apply(
function: Callable[[Series], Series] | Callable[[Any], Any],
return_dtype: PolarsDataType | None = None,
*,
skip_nulls: bool = True,
pass_name: bool = False,
strategy: MapElementsStrategy = 'thread_local',
) → Self[source]#

Apply a custom/user-defined function (UDF) in a GroupBy or Projection context.

Deprecated since version 0.19.0: This method has been renamed to Expr.map_elements().

Parameters:
function

Lambda/ function to apply.

return_dtype

Dtype of the output Series. If not set, the dtype will be polars.Unknown.

skip_nulls

Don’t apply the function over values that contain nulls. This is faster.

pass_name

Pass the Series name to the custom function This is more expensive.

strategy{‘thread_local’, ‘threading’}

This functionality is in alpha stage. This may be removed /changed without it being considered a breaking change.

  • ‘thread_local’: run the python function on a single thread.

  • ‘threading’: run the python function on separate threads. Use with care as this can slow performance. This might only speed up your code if the amount of work per element is significant and the python function releases the GIL (e.g. via calling a c function)