def apply(
exprs: list[str | pli.Expr],
f: Callable[[list[pli.Series]], pli.Series | Any],
return_dtype: type[DataType] | None = None,
) -> pli.Expr:
"""
Apply a custom function in a GroupBy context.
Depending on the context it has the following behavior:
* Select
Don't use apply, use `map`
* GroupBy
expected type `f`: Callable[[Series], Series]
Applies a python function over each group.
Parameters
----------
exprs
Input Series to f
f
Function to apply over the input
return_dtype
dtype of the output Series
Returns
-------
Expr
"""
exprs = pli.selection_to_pyexpr_list(exprs)
return pli.wrap_expr(_map_mul(exprs, f, return_dtype, apply_groups=True))
def apply(
exprs: List[Union[str, "pli.Expr"]],
f: Callable[[List["pli.Series"]], Union["pli.Series", Any]],
return_dtype: Optional[Type[DataType]] = None,
) -> "pli.Expr":
"""
Apply a custom function in a GroupBy context.
Depending on the context it has the following behavior:
## Context
* Select/Project
Don't do this, use `map`
* GroupBy
expected type `f`: Callable[[Series], Series]
Applies a python function over each group.
Parameters
----------
exprs
Input Series to f
f
Function to apply over the input
return_dtype
dtype of the output Series
Returns
-------
Expr
"""
exprs = pli.selection_to_pyexpr_list(exprs)
return pli.wrap_expr(_map_mul(exprs, f, return_dtype, apply_groups=True))
def map(
exprs: list[str] | list[pli.Expr],
f: Callable[[list[pli.Series]], pli.Series],
return_dtype: type[DataType] | None = None,
) -> pli.Expr:
"""
Map a custom function over multiple columns/expressions and produce a single Series result.
Parameters
----------
exprs
Input Series to f
f
Function to apply over the input
return_dtype
dtype of the output Series
Returns
-------
Expr
"""
exprs = pli.selection_to_pyexpr_list(exprs)
return pli.wrap_expr(_map_mul(exprs, f, return_dtype, apply_groups=False))