# pandas.Series.sort_values

`Series.``sort_values`(axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last')

  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.

  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     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

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