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.name
with 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.name
attribute.- **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