pyspark.pandas.Series.sort_values¶
-
Series.
sort_values
(ascending: bool = True, inplace: bool = False, na_position: str = 'last', ignore_index: bool = False) → Optional[pyspark.pandas.series.Series][source]¶ Sort by the values.
Sort a Series in ascending or descending order by some criterion.
- Parameters
- ascendingbool or list of bool, default True
Sort ascending vs. descending. Specify list for multiple sort orders. If this is a list of bools, must match the length of the by.
- inplacebool, default False
if True, perform operation in-place
- na_position{‘first’, ‘last’}, default ‘last’
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 3.4.0.
- Returns
- sorted_objSeries ordered by values.
Examples
>>> s = ps.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 descending order and ignoring index
>>> s.sort_values(ascending=False, ignore_index=True) 0 10.0 1 5.0 2 3.0 3 1.0 4 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 = ps.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