pandas.DataFrame.rename

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

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 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.

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