BPt.Dataset.set_axis#

Dataset.set_axis(labels, *, axis=0, inplace=_NoDefault.no_default, copy=_NoDefault.no_default)[source]#

Assign desired index to given axis.

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

Parameters
labelslist-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. For Series this parameter is unused and defaults to 0.

inplacebool, default False

Whether to return a new DataFrame instance.

Deprecated since version 1.5.0.

copybool, default True

Whether to make a copy of the underlying data.

New in version 1.5.0.

Returns
renamedDataFrame or None

An object of type DataFrame or None if inplace=True.

See also

DataFrame.rename_axis

Alter the name of the index or columns.

Examples

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

Change the row labels.

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

Change the column labels.

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

Now, update the labels without copying the underlying data.

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