pandas.Series.rename

Series.rename(self, index=None, **kwargs) [source]

Alter Series index labels or name.

Function / dict values must be unique (1-to-1). Labels not contained in a dict / Series will be left as-is. Extra labels listed don’t throw an error.

Alternatively, change Series.name with a scalar value.

See the user guide for more.

Parameters:

index : scalar, hashable sequence, dict-like or function, optional dict-like or functions are transformations to apply to the index. Scalar or hashable sequence-like will alter the Series.name attribute. copy : bool, default True Whether to copy underlying data. inplace : bool, default False Whether to return a new Series. If True then value of copy is ignored. level : int or level name, default None In case of a MultiIndex, only rename labels in the specified level.

Returns:

Series Series with index labels or name altered.

See also

Series.rename_axis

Set the name of the axis.

Examples

>>> s = pd.Series([1, 2, 3])
>>> s
0    1
1    2
2    3
dtype: int64
>>> s.rename("my_name")  # scalar, changes Series.name
0    1
1    2
2    3
Name: my_name, dtype: int64
>>> s.rename(lambda x: x ** 2)  # function, changes labels
0    1
1    2
4    3
dtype: int64
>>> s.rename({1: 3, 2: 5})  # mapping, changes labels
0    1
3    2
5    3
dtype: int64