pandas.DataFrame.set_axis#

DataFrame.set_axis(labels, *, axis=0, copy=None)[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.
copybool, default True: Whether to make a copy of the underlying data.

Note

The copy keyword will change behavior in pandas 3.0. Copy-on-Write will be enabled by default, which means that all methods with a copy keyword will use a lazy copy mechanism to defer the copy and ignore the copy keyword. The copy keyword will be removed in a future version of pandas.

You can already get the future behavior and improvements through enabling copy on write pd.options.mode.copy_on_write = True

Returns:

See also

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