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masked_reductions.py is for reduction algorithms using a mask-based approach
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for missing values.
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é )Ú annotations)ÚCallableN)Úmissing)ÚAxisIntÚnpt)Úcheck_below_min_countT)ÚskipnaÚ min_countÚaxisr z
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Sum, mean or product for 1D masked array.
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|
Parameters
|
----------
|
func : np.sum or np.prod
|
values : np.ndarray
|
Numpy array with the values (can be of any dtype that support the
|
operation).
|
mask : np.ndarray[bool]
|
Boolean numpy array (True values indicate missing values).
|
skipna : bool, default True
|
Whether to skip NA.
|
min_count : int, default 0
|
The required number of valid values to perform the operation. If fewer than
|
``min_count`` non-NA values are present the result will be NA.
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axis : int, optional, default None
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Reduction for 1D masked array.
|
|
Parameters
|
----------
|
func : np.min or np.max
|
values : np.ndarray
|
Numpy array with the values (can be of any dtype that support the
|
operation).
|
mask : np.ndarray[bool]
|
Boolean numpy array (True values indicate missing values).
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skipna : bool, default True
|
Whether to skip NA.
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axis : int, optional, default None
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