DataFrame.rename(mapper=None, index=None, columns=None, axis='index', copy=True, inplace=False, level=None, errors='ignore')#

Rename columns or index 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.

  • mapper (dict-like or function) – Dict-like or function 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 ({0 or 'index', 1 or 'columns'}, default 0) – 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 modify the DataFrame rather than creating a new one. 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.


DataFrame with the renamed axis labels or None if inplace=True.

Return type

DataFrame or None


KeyError – If any of the labels is not found in the selected axis and “errors=’raise’”.

See also


Set the name of the axis.


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

This docstring was copied from pandas.core.frame.DataFrame.