# mars.dataframe.Series.sort_values#

Series.sort_values(axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last', ignore_index=False, parallel_kind='PSRS', psrs_kinds=None)#

Sort by the values.

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

Parameters
• series (input Series.) –

• 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.

• ignore_index (bool, default False) – If True, the resulting axis will be labeled 0, 1, …, n - 1.

Returns

Series ordered by values.

Return type

Series

Examples

```>>> import mars.dataframe as md
>>> raw = pd.Series([np.nan, 1, 3, 10, 5])
>>> s = md.Series(raw)
>>> s.execute()
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).execute()
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).execute()
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.execute()
3    10.0
4     5.0
2     3.0
1     1.0
0     NaN
dtype: float64
```

Sort values putting NAs first