# pandas.Series.rename

`Series.``rename`(index=None, **kwargs)

  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 : boolean, default True

  > Also copy underlying data

  inplace : boolean, default False

  > Whether to return a new %(klass)s. 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: | renamed : Series (new object)

  See also

  `pandas.Series.rename_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

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