pandas 1.4.2

ParametersReturns
_get_cythonized_result(self, base_func: 'Callable', cython_dtype: 'np.dtype', numeric_only: 'bool | lib.NoDefault' = <no_default>, needs_counts: 'bool' = False, needs_nullable: 'bool' = False, needs_mask: 'bool' = False, pre_processing=None, post_processing=None, **kwargs)

Parameters

base_func : callable, Cythonized function to be called
cython_dtype : np.dtype

Type of the array that will be modified by the Cython call.

numeric_only : bool, default True

Whether only numeric datatypes should be computed

needs_counts : bool, default False

Whether the counts should be a part of the Cython call

needs_mask : bool, default False

Whether boolean mask needs to be part of the Cython call signature

needs_nullable : bool, default False

Whether a bool specifying if the input is nullable is part of the Cython call signature

pre_processing : function, default None

Function to be applied to :None:None:`values` prior to passing to Cython. Function should return a tuple where the first element is the values to be passed to Cython and the second element is an optional type which the values should be converted to after being returned by the Cython operation. This function is also responsible for raising a TypeError if the values have an invalid type. Raises if :None:None:`needs_values` is False.

post_processing : function, default None

Function to be applied to result of Cython function. Should accept an array of values as the first argument and type inferences as its second argument, i.e. the signature should be (ndarray, Type). If :None:None:`needs_nullable=True`, a third argument should be :None:None:`nullable`, to allow for processing specific to nullable values.

**kwargs : dict

Extra arguments to be passed back to Cython funcs

Returns

`Series` or `DataFrame` with filled values

Get result for Cythonized functions.

Examples

See :

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File: /pandas/core/groupby/groupby.py#3262
type: <class 'function'>
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