pyspark.pandas.Series.rename_axis

Series.rename_axis(mapper: Optional[Any] = None, index: Optional[Any] = None, inplace: bool = False) → Optional[pyspark.pandas.series.Series]

Set the name of the axis for the index or columns.

Parameters

mapper, indexscalar, list-like, dict-like or function, optional

A scalar, list-like, dict-like or functions transformations to apply to the index values.

inplacebool, default False

Modifies the object directly, instead of creating a new Series.

Returns

Series, or None if inplace is True.

See also

Series.rename

Alter Series index labels or name.

DataFrame.rename

Alter DataFrame index labels or name.

Index.rename

Set new names on index.

Examples

>>> s = ps.Series(["dog", "cat", "monkey"], name="animal")
>>> s  
0       dog
1       cat
2    monkey
Name: animal, dtype: object
>>> s.rename_axis("index").sort_index()  
index
0       dog
1       cat
2    monkey
Name: animal, dtype: object

MultiIndex

>>> index = pd.MultiIndex.from_product([['mammal'],
...                                        ['dog', 'cat', 'monkey']],
...                                       names=['type', 'name'])
>>> s = ps.Series([4, 4, 2], index=index, name='num_legs')
>>> s  
type    name
mammal  dog       4
        cat       4
        monkey    2
Name: num_legs, dtype: int64
>>> s.rename_axis(index={'type': 'class'}).sort_index()  
class   name
mammal  cat       4
        dog       4
        monkey    2
Name: num_legs, dtype: int64
>>> s.rename_axis(index=str.upper).sort_index()  
TYPE    NAME
mammal  cat       4
        dog       4
        monkey    2
Name: num_legs, dtype: int64

pyspark.pandas.Series.rename pyspark.pandas.Series.reindex