pandas.DataFrame.set_axis
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DataFrame.set_axis(labels, axis=0, inplace=None)
[source] -
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
andaxis
, consistent with the rest of pandas API. Previously, theaxis
andlabels
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
-
pandas.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
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Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.DataFrame.set_axis.html