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| -rw-r--r-- | doc/neps/missing-data.rst | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/doc/neps/missing-data.rst b/doc/neps/missing-data.rst index 66d70ae48..0dde5bb0f 100644 --- a/doc/neps/missing-data.rst +++ b/doc/neps/missing-data.rst @@ -176,8 +176,8 @@ provides a starting point. For example,:: - >>> np.array([1.0, 2.0, np.NA, 7.0], masked=True) - array([1., 2., NA, 7.], masked=True) + >>> np.array([1.0, 2.0, np.NA, 7.0], namasked=True) + array([1., 2., NA, 7.], namasked=True) >>> np.array([1.0, 2.0, np.NA, 7.0], dtype='NA[f8]') array([1., 2., NA, 7.], dtype='NA[<f8]') @@ -189,14 +189,14 @@ It may be worth overloading the np.NA __call__ method to accept a dtype, returning a zero-dimensional array with a missing value of that dtype. Without doing this, NA printouts would look like:: - >>> np.sum(np.array([1.0, 2.0, np.NA, 7.0], masked=True)) - array(NA, dtype='float64', masked=True) + >>> np.sum(np.array([1.0, 2.0, np.NA, 7.0], namasked=True)) + array(NA, dtype='float64', namasked=True) >>> np.sum(np.array([1.0, 2.0, np.NA, 7.0], dtype='NA[f8]')) array(NA, dtype='NA[<f8]') but with this, they could be printed as:: - >>> np.sum(np.array([1.0, 2.0, np.NA, 7.0], masked=True)) + >>> np.sum(np.array([1.0, 2.0, np.NA, 7.0], namasked=True)) NA('float64') >>> np.sum(np.array([1.0, 2.0, np.NA, 7.0], dtype='NA[f8]')) NA('NA[<f8]') @@ -446,7 +446,7 @@ their behavior is through a series of examples:: True >>> np.all(np.array([True, True, True], namasked=True)) - False + True >>> np.all(np.array([True, NA, True], namasked=True)) NA >>> np.all(np.array([False, NA, True], namasked=True)) |