pandas.Series.sort_values¶

Series.sort_values(self, axis=0, ascending=True, inplace: bool = False, kind: str = 'quicksort', na_position: str = 'last', ignore_index: bool = False)[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.
ascendingbool, default True: If True, sort values in ascending order, otherwise descending.
inplacebool, 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.
ignore_indexbool, default False: If True, the resulting axis will be labeled 0, 1, …, n - 1.

New in version 1.0.0.

Returns

Series: Series ordered by values.

See also

Series.sort_index: Sort by the Series indices.
DataFrame.sort_values: Sort DataFrame by the values along either axis.
DataFrame.sort_index: Sort DataFrame by indices.

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)
   1.0
   3.0
   5.0
  10.0
   NaN
dtype: float64

Sort values descending order

>>> s.sort_values(ascending=False)
  10.0
   5.0
   3.0
   1.0
   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')
   NaN
   1.0
   3.0
   5.0
  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()
  a
  b
  c
  d
  z
dtype: object