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Mar 10, 2018
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fix reviewed pull request #2

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107 changes: 55 additions & 52 deletions pandas/core/series.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1890,21 +1890,24 @@ def sort_values(self, axis=0, ascending=True, inplace=False,
"""
Sort by the Series values.

Sort (or order) a Series into ascending or descending order by some criterion.
Sort (or order) a Series in ascending or descending order by some
criterion.

Parameters
----------
axis : {0 or ‘index’}, default 0
Axis to direct sorting.
Axis to direct sorting. The value `index` is accepted for
compatibility with DataFrame.sort_values.
ascending : bool, default True
If `True` sort values into ascending order, otherwise descending.
If `True` sort values in ascending order, otherwise descending.
inplace : bool, default False
If True, perform operation in-place.
kind : {‘quicksort’, ‘mergesort’ or ‘heapsort’}, default ‘quicksort’
Choice of sorting algorithm. See also ndarray.np.sort [1]_ for more information. `mergesort` is the only stable
algorithm.
Choice of sorting algorithm. See also :func:`np.sort` for more
information. `mergesort` is the only stable algorithm.
na_position : {'first' or 'last'}, default 'last'
Argument `first` puts NaNs at the beginning, `last` puts NaNs at the end.
Argument `first` puts NaNs at the beginning, `last` puts NaNs at
the end.

Returns
-------
Expand All @@ -1917,76 +1920,76 @@ def sort_values(self, axis=0, ascending=True, inplace=False,
DataFrame.sort_index : Sort DataFrame by indices.
DataFrame.sort_values : Sort by the values along either axis.

References
----------
.. [1] https://docs.scipy.org/doc/numpy/reference/generated/numpy.sort.html

Examples
--------
>>> s = pd.Series([np.nan, 1, 232, 323, 1, 2, 3, 45])
>>> s = pd.Series([np.nan, 1, 3, 5, 10])
>>> s
0 NaN
1 1.0
2 232.0
3 323.0
4 1.0
5 2.0
6 3.0
7 45.0
0 NaN
1 1.0
2 3.0
3 5.0
4 10.0
dtype: float64

Sort values ascending order
Sort values ascending order (default behaviour)

>>> s.sort_values(ascending=True)
1 1.0
4 1.0
5 2.0
6 3.0
7 45.0
2 232.0
3 323.0
0 NaN
1 1.0
2 3.0
3 5.0
4 10.0
0 NaN
dtype: float64

Sort values descending order

>>> s.sort_values(ascending=False)
3 323.0
2 232.0
7 45.0
6 3.0
5 2.0
4 1.0
1 1.0
0 NaN
4 10.0
3 5.0
2 3.0
1 1.0
0 NaN
dtype: float64

Sort values inplace

>>> s.sort_values(ascending=False, inplace=True)
>>> s
3 323.0
2 232.0
7 45.0
6 3.0
5 2.0
4 1.0
1 1.0
0 NaN
4 10.0
3 5.0
2 3.0
1 1.0
0 NaN
dtype: float64

Sort values putting NAs first

>>> s.sort_values(na_position='first')
0 NaN
4 1.0
1 1.0
5 2.0
6 3.0
7 45.0
2 232.0
3 323.0
0 NaN
1 1.0
2 3.0
3 5.0
4 10.0
dtype: float64

Sort a series of strings

>>> s = pd.Series(['z', 'b', 'd', 'a', 'c'])
>>> s
0 z
1 b
2 d
3 a
4 c
dtype: object

>>> s.sort_values()
3 a
1 b
4 c
2 d
0 z
dtype: object
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
axis = self._get_axis_number(axis)
Expand Down