pandas.Series.set_axis

Series.set_axis(labels, axis=0, inplace=None)

Assign desired index to given axis.

Indexes for column or row labels can be changed by assigning a list-like or Index.

Changed in version 0.21.0: The signature is now labels and axis, consistent with the rest of pandas API. Previously, the axis and labels arguments were respectively the first and second positional arguments.

Parameters:

labels : list-like, Index

The values for the new index.

axis : {0 or ‘index’, 1 or ‘columns’}, default 0

The axis to update. The value 0 identifies the rows, and 1 identifies the columns.

inplace : boolean, default None

Whether to return a new %(klass)s instance.

Warning

inplace=None currently falls back to to True, but in a future version, will default to False. Use inplace=True explicitly rather than relying on the default.

Returns:

renamed : %(klass)s or None

An object of same type as caller if inplace=False, None otherwise.

See also

DataFrame.rename_axis

Alter the name of the index or columns.

Examples

Series

>>> s = pd.Series([1, 2, 3])
>>> s
0    1
1    2
2    3
dtype: int64

>>> s.set_axis(['a', 'b', 'c'], axis=0, inplace=False)
a    1
b    2
c    3
dtype: int64

The original object is not modified.

>>> s
0    1
1    2
2    3
dtype: int64

DataFrame

>>> df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})

Change the row labels.

>>> df.set_axis(['a', 'b', 'c'], axis='index', inplace=False)
   A  B
a  1  4
b  2  5
c  3  6

Change the column labels.

>>> df.set_axis(['I', 'II'], axis='columns', inplace=False)
   I  II
0  1   4
1  2   5
2  3   6

Now, update the labels inplace.

>>> df.set_axis(['i', 'ii'], axis='columns', inplace=True)
>>> df
   i  ii
0  1   4
1  2   5
2  3   6