pandas.Series.set_axis — pandas 0.24.0rc1 documentation (original) (raw)
Series. 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 and axis, consistent with the rest of pandas API. Previously, the axis and labelsarguments 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. |
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