@rewrite_axis_style_signature('<STR_LIT>', [('<STR_LIT>', True),<EOL>('<STR_LIT>', False),<EOL>('<STR_LIT>', None),<EOL>('<STR_LIT>', '<STR_LIT:ignore>')])<EOL><INDENT>def rename(self, *args, **kwargs):<DEDENT>
axes = validate_axis_style_args(self, args, kwargs, '<STR_LIT>', '<STR_LIT>')<EOL>kwargs.update(axes)<EOL>kwargs.pop('<STR_LIT>', None)<EOL>kwargs.pop('<STR_LIT>', None)<EOL>return super().rename(**kwargs)<EOL>
Alter axes labels.

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.

See the :ref:`user guide <basics.rename>` for more.

Parameters
----------
mapper : dict-like or function
    Dict-like or functions transformations to apply to
    that axis' values. Use either ``mapper`` and ``axis`` to
    specify the axis to target with ``mapper``, or ``index`` and
    ``columns``.
index : dict-like or function
    Alternative to specifying axis (``mapper, axis=0``
    is equivalent to ``index=mapper``).
columns : dict-like or function
    Alternative to specifying axis (``mapper, axis=1``
    is equivalent to ``columns=mapper``).
axis : int or str
    Axis to target with ``mapper``. Can be either the axis name
    ('index', 'columns') or number (0, 1). The default is 'index'.
copy : bool, default True
    Also copy underlying data.
inplace : bool, default False
    Whether to return a new DataFrame. 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.
errors : {'ignore', 'raise'}, default 'ignore'
    If 'raise', raise a `KeyError` when a dict-like `mapper`, `index`,
    or `columns` contains labels that are not present in the Index
    being transformed.
    If 'ignore', existing keys will be renamed and extra keys will be
    ignored.

Returns
-------
DataFrame
    DataFrame with the renamed axis labels.

Raises
------
KeyError
    If any of the labels is not found in the selected axis and
    "errors='raise'".

See Also
--------
DataFrame.rename_axis : Set the name of the axis.

Examples
--------

``DataFrame.rename`` supports two calling conventions

* ``(index=index_mapper, columns=columns_mapper, ...)``
* ``(mapper, axis={'index', 'columns'}, ...)``

We *highly* recommend using keyword arguments to clarify your
intent.

>>> df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
>>> df.rename(index=str, columns={"A": "a", "B": "c"})
   a  c
0  1  4
1  2  5
2  3  6

>>> df.rename(index=str, columns={"A": "a", "C": "c"})
   a  B
0  1  4
1  2  5
2  3  6

>>> df.rename(index=str, columns={"A": "a", "C": "c"}, errors="raise")
Traceback (most recent call last):
KeyError: ['C'] not found in axis

Using axis-style parameters

>>> df.rename(str.lower, axis='columns')
   a  b
0  1  4
1  2  5
2  3  6

>>> df.rename({1: 2, 2: 4}, axis='index')
   A  B
0  1  4
2  2  5
4  3  6