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Diffstat (limited to 'doc/neps/c-masked-array.rst')
| -rw-r--r-- | doc/neps/c-masked-array.rst | 31 |
1 files changed, 25 insertions, 6 deletions
diff --git a/doc/neps/c-masked-array.rst b/doc/neps/c-masked-array.rst index 3384baa33..d75025d51 100644 --- a/doc/neps/c-masked-array.rst +++ b/doc/neps/c-masked-array.rst @@ -319,14 +319,33 @@ Reduction operations like 'sum', 'prod', 'min', and 'max' will operate consistently with the idea that a masked value exists, but its value is unknown. -An optional parameter 'skipna=False' will be added to those functions +An optional parameter 'skipna=' will be added to those functions which can interpret it appropriately to do the operation as if just -the unmasked values existed. When all the input values are masked, +the unmasked values existed. + +With 'skipna=True', when all the input values are masked, 'sum' and 'prod' will produce the additive and multiplicative identities -respectively, while 'min' and 'max' will produce masked values. With -this parameter enabled, statistics operations which require a count, -like 'mean' and 'std' will also use the unmasked value counts for -their calculations, and produce masked values when all the inputs are masked. +respectively, while 'min' and 'max' will produce masked values. +Statistics operations which require a count, like 'mean' and 'std' +will also use the unmasked value counts for their calculations if +'skipna=True', and produce masked values when all the inputs are masked. + +Some examples:: + + >>> a = np.array([1., 3., np.NA, 7.], masked=True) + >>> np.sum(a) + array(NA, dtype='<f8', masked=True) + >>> np.sum(a, skipna=True) + 11.0 + >>> np.mean(a) + array(NA, dtype='<f8', masked=True) + >>> np.mean(a) + 3.6666666666666665 + >>> a = np.array([np.NA, np.NA], dtype='f8', masked=True) + >>> np.sum(a, skipna=True) + 0.0 + >>> np.max(a, skipna=True) + array(NA, dtype='<f8', masked=True) PEP 3118 ======== |