DataFrame.rename(mapper=None, index=None, columns=None, axis=None, copy=True, inplace=False, level=None)
[source]
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 user guide for more.
Parameters: |
mapper, index, columns : dict-like or function, optional dict-like or functions transformations to apply to that axis’ values. Use either axis : int or str, optional Axis to target with copy : boolean, default True Also copy underlying data inplace : boolean, 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. |
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Returns: |
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See also
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
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
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Licensed under the 3-clause BSD License.
http://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.DataFrame.rename.html