pandas.DataFrame.rename
-
DataFrame.rename(self, mapper=None, index=None, columns=None, axis=None, copy=True, inplace=False, level=None, errors='ignore')
[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 : dict-like or function
-
Dict-like or functions transformations to apply to that axis’ values. Use either
mapper
andaxis
to specify the axis to target withmapper
, orindex
andcolumns
. -
index : dict-like or function
-
Alternative to specifying axis (
mapper, axis=0
is equivalent toindex=mapper
). -
columns : dict-like or function
-
Alternative to specifying axis (
mapper, axis=1
is equivalent tocolumns=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-likemapper
,index
, orcolumns
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.
Rename columns using a mapping:
>>> df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}) >>> df.rename(columns={"A": "a", "B": "c"}) a c 0 1 4 1 2 5 2 3 6
Rename index using a mapping:
>>> df.rename(index={0: "x", 1: "y", 2: "z"}) A B x 1 4 y 2 5 z 3 6
Cast index labels to a different type:
>>> df.index RangeIndex(start=0, stop=3, step=1) >>> df.rename(index=str).index Index(['0', '1', '2'], dtype='object')
>>> df.rename(columns={"A": "a", "B": "b", "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
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© 2008–2012, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.25.0/reference/api/pandas.DataFrame.rename.html