pandas.Series.rename#
- Series.rename(index=None, *, axis=None, copy=True, inplace=False, level=None, errors='ignore')[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.namewith a scalar value.- See the user guide for more. - Parameters
- axis{0 or “index”}
- Unused. Accepted for compatibility with DataFrame method only. 
- indexscalar, hashable sequence, dict-like or function, optional
- Functions or dict-like are transformations to apply to the index. Scalar or hashable sequence-like will alter the - Series.nameattribute.
- **kwargs
- Additional keyword arguments passed to the function. Only the “inplace” keyword is used. 
 
- Returns
- Series or None
- Series with index labels or name altered or None if - inplace=True.
 
 - See also - DataFrame.rename
- Corresponding DataFrame method. 
- 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