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DOC: update the isna, isnull, notna and notnull docstring #20459

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Mar 26, 2018
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DOC: update the isna, isnull, notna and notnull docstring #20459

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DOC: update the isna, isnull, notna, notnull docstring
Cheukting Mar 22, 2018
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improve docstring
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Furthe improve docstring
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Improve more on docstring
Cheukting Mar 22, 2018
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DOC: Improve the docstrings of isna, isnull, notna, notnull
Mar 26, 2018
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Updates.
TomAugspurger Mar 26, 2018
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36 changes: 35 additions & 1 deletion pandas/core/dtypes/missing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,12 @@


def isna(obj):
"""Detect missing values (NaN in numeric arrays, None/NaN in object arrays)
"""Detect missing values for an array
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End with a .


This function takes an array-like object, for each element, if it is
a missing value (NaN in numeric arrays, None/NaN in object arrays)
the correisponding element of the output boolean array will be true,
otherwise false.

Parameters
----------
Expand All @@ -46,6 +51,18 @@ def isna(obj):
--------
pandas.notna: boolean inverse of pandas.isna
pandas.isnull: alias of isna

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Add Series.isna, DataFrame.isna, and Index.isna.

Examples
--------
>>> df = pd.DataFrame([[1, pd.np.nan, 3], [4, 5, pd.np.nan]])
>>> df
0 1 2
0 1 NaN 3.0
1 4 5.0 NaN
>>> pd.isna(df)
0 1 2
0 False True False
1 False False True
"""
return _isna(obj)

Expand Down Expand Up @@ -200,6 +217,11 @@ def notna(obj):
"""Replacement for numpy.isfinite / -numpy.isnan which is suitable for use
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Can you shorten this to a single line? Can be similar to you docstring for isna, just flipped.

on object arrays.

This function takes an array-like object, for each element, if it is *not*
a missing.value (NaN in numeric arrays, None/NaN in object arrays) the
correisponding element of the output boolean array will be true,
otherwise false.

Parameters
----------
arr : ndarray or object value
Expand All @@ -215,6 +237,18 @@ def notna(obj):
--------
pandas.isna : boolean inverse of pandas.notna
pandas.notnull : alias of notna

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Add Series.notna, DataFrame.notna, and Index.notna

Examples
--------
>>> df = pd.DataFrame([[1, pd.np.nan, 3], [4, 5, pd.np.nan]])
>>> df
0 1 2
0 1 NaN 3.0
1 4 5.0 NaN
>>> pd.notna(df)
0 1 2
0 True False True
1 True True False
"""
res = isna(obj)
if is_scalar(res):
Expand Down