pandas.Series.sort_values — pandas 0.25.3 documentation (original) (raw)

Series. sort_values(self, axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last')[source]¶

Sort by the values.

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

Parameters:	axis : {0 or ‘index’}, default 0 Axis to direct sorting. The value ‘index’ is accepted for compatibility with DataFrame.sort_values. ascending : bool, default True 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 numpy.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.
Returns:	Series Series ordered by values.

Parameters:

axis : {0 or ‘index’}, default 0 Axis to direct sorting. The value ‘index’ is accepted for compatibility with DataFrame.sort_values. ascending : bool, default True 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 numpy.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.

Returns:

Series Series ordered by values.

Examples

s = pd.Series([np.nan, 1, 3, 10, 5]) s 0 NaN 1 1.0 2 3.0 3 10.0 4 5.0 dtype: float64

Sort values ascending order (default behaviour)

s.sort_values(ascending=True) 1 1.0 2 3.0 4 5.0 3 10.0 0 NaN dtype: float64

Sort values descending order

s.sort_values(ascending=False) 3 10.0 4 5.0 2 3.0 1 1.0 0 NaN dtype: float64

Sort values inplace

s.sort_values(ascending=False, inplace=True) s 3 10.0 4 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 1 1.0 2 3.0 4 5.0 3 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