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masked_accumulations.py is for accumulation algorithms using a mask-based approach
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for missing values.
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é )Ú annotations)ÚCallableN)Únpt)Ú is_bool_dtypeÚis_float_dtypeÚis_integer_dtypeT©Úskipnar z
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np.ndarrayznpt.NDArray[np.bool_]Úbool)ÚfuncÚvaluesÚmaskr c C sÒ t |rt |jj¡}n@t|r0t |jj¡}n(t|rFt tj¡}nt d|jj z,tj
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Accumulations for 1D masked array.
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We will modify values in place to replace NAs with the appropriate fill value.
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Parameters
|
----------
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func : np.cumsum, np.cumprod, np.maximum.accumulate, np.minimum.accumulate
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values : np.ndarray
|
Numpy array with the values (can be of any dtype that support the
|
operation).
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mask : np.ndarray
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Boolean numpy array (True values indicate missing values).
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skipna : bool, default True
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Whether to skip NA.
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z)No masked accumulation defined for dtype é r zNo accumulation for z implemented on BaseMaskedArray)r ÚnpZfinfoZdtypeÚtyper Ziinfor Zuint8ÚNotImplementedErrorÚcumprodÚmaximumÚ
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dtype_infoZ
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fill_value© r úcd:\z\workplace\vscode\pyvenv\venv\Lib\site-packages\pandas/core/array_algos/masked_accumulations.pyÚ _cum_func s< ÿ üû
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r ©r r r c C s t tj| ||dS ©Nr )r r r r r r r r O s r c C s t tj| ||dS r )r r r r r r r r S s r c C s t tjj| ||dS r )r r r r r r r r ÚcumminW s r c C s t tjj| ||dS r )r r r r r r r r Úcummax[ s r )Ú__doc__Ú
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__future__r Útypingr Únumpyr Zpandas._typingr Zpandas.core.dtypes.commonr r r r r r r r r r r r Ú<module> s û:
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