pandas.Series.sort_values

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.

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.

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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