pyspark.pandas.Series.rename_axis#

Series.rename_axis(mapper=None, index=None, inplace=False)[source]#

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