pandas.Series.sort_index — pandas 0.24.0rc1 documentation (original) (raw)

Series. sort_index(axis=0, level=None, ascending=True, inplace=False, kind='quicksort', na_position='last', sort_remaining=True)[source]¶

Sort Series by index labels.

Returns a new Series sorted by label if inplace argument isFalse, otherwise updates the original series and returns None.

Parameters:	axis : int, default 0 Axis to direct sorting. This can only be 0 for Series. level : int, optional If not None, sort on values in specified index level(s). ascending : bool, default true Sort ascending vs. descending. inplace : bool, default False If True, perform operation in-place. kind : {‘quicksort’, ‘mergesort’, ‘heapsort’}, default ‘quicksort’ Choice of sorting algorithm. See also numpy.sort() for more information. ‘mergesort’ is the only stable algorithm. For DataFrames, this option is only applied when sorting on a single column or label. na_position : {‘first’, ‘last’}, default ‘last’ If ‘first’ puts NaNs at the beginning, ‘last’ puts NaNs at the end. Not implemented for MultiIndex. sort_remaining : bool, default True If true and sorting by level and index is multilevel, sort by other levels too (in order) after sorting by specified level.
Returns:	pandas.Series The original Series sorted by the labels

Parameters:

axis : int, default 0 Axis to direct sorting. This can only be 0 for Series. level : int, optional If not None, sort on values in specified index level(s). ascending : bool, default true Sort ascending vs. descending. inplace : bool, default False If True, perform operation in-place. kind : {‘quicksort’, ‘mergesort’, ‘heapsort’}, default ‘quicksort’ Choice of sorting algorithm. See also numpy.sort() for more information. ‘mergesort’ is the only stable algorithm. For DataFrames, this option is only applied when sorting on a single column or label. na_position : {‘first’, ‘last’}, default ‘last’ If ‘first’ puts NaNs at the beginning, ‘last’ puts NaNs at the end. Not implemented for MultiIndex. sort_remaining : bool, default True If true and sorting by level and index is multilevel, sort by other levels too (in order) after sorting by specified level.

Returns:

pandas.Series The original Series sorted by the labels

Examples

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

Sort Descending

s.sort_index(ascending=False) 4 d 3 a 2 b 1 c dtype: object

Sort Inplace

s.sort_index(inplace=True) s 1 c 2 b 3 a 4 d dtype: object

By default NaNs are put at the end, but use na_position to place them at the beginning

s = pd.Series(['a', 'b', 'c', 'd'], index=[3, 2, 1, np.nan]) s.sort_index(na_position='first') NaN d 1.0 c 2.0 b 3.0 a dtype: object

Specify index level to sort

arrays = [np.array(['qux', 'qux', 'foo', 'foo', ... 'baz', 'baz', 'bar', 'bar']), ... np.array(['two', 'one', 'two', 'one', ... 'two', 'one', 'two', 'one'])] s = pd.Series([1, 2, 3, 4, 5, 6, 7, 8], index=arrays) s.sort_index(level=1) bar one 8 baz one 6 foo one 4 qux one 2 bar two 7 baz two 5 foo two 3 qux two 1 dtype: int64

Does not sort by remaining levels when sorting by levels

s.sort_index(level=1, sort_remaining=False) qux one 2 foo one 4 baz one 6 bar one 8 qux two 1 foo two 3 baz two 5 bar two 7 dtype: int64