pandas.DataFrame.rename_axis — pandas 0.24.0rc1 documentation (original) (raw)
DataFrame. rename_axis(mapper=None, index=None, columns=None, axis=None, copy=True, inplace=False)[source]¶
Set the name of the axis for the index or columns.
| Parameters: | mapper : scalar, list-like, optional Value to set the axis name attribute. index, columns : scalar, list-like, dict-like or function, optional A scalar, list-like, dict-like or functions transformations to apply to that axis’ values. Use either mapper and axis to specify the axis to target with mapper, or indexand/or columns. Changed in version 0.24.0. axis : {0 or ‘index’, 1 or ‘columns’}, default 0 The axis to rename. copy : bool, default True Also copy underlying data. inplace : bool, default False Modifies the object directly, instead of creating a new Series or DataFrame. |
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| Returns: | Series, DataFrame, or None The same type as the caller or None if inplace is True. |
Notes
Prior to version 0.21.0, rename_axis could also be used to change the axis labels by passing a mapping or scalar. This behavior is deprecated and will be removed in a future version. Use renameinstead.
DataFrame.rename_axis supports two calling conventions
(index=index_mapper, columns=columns_mapper, ...)(mapper, axis={'index', 'columns'}, ...)
The first calling convention will only modify the names of the index and/or the names of the Index object that is the columns. In this case, the parameter copy is ignored.
The second calling convention will modify the names of the the corresponding index if mapper is a list or a scalar. However, if mapper is dict-like or a function, it will use the deprecated behavior of modifying the axis labels.
We highly recommend using keyword arguments to clarify your intent.
Examples
Series
s = pd.Series(["dog", "cat", "monkey"]) s 0 dog 1 cat 2 monkey dtype: object s.rename_axis("animal") animal 0 dog 1 cat 2 monkey dtype: object
DataFrame
df = pd.DataFrame({"num_legs": [4, 4, 2], ... "num_arms": [0, 0, 2]}, ... ["dog", "cat", "monkey"]) df num_legs num_arms dog 4 0 cat 4 0 monkey 2 2 df = df.rename_axis("animal") df num_legs num_arms animal dog 4 0 cat 4 0 monkey 2 2 df = df.rename_axis("limbs", axis="columns") df limbs num_legs num_arms animal dog 4 0 cat 4 0 monkey 2 2
MultiIndex
df.index = pd.MultiIndex.from_product([['mammal'], ... ['dog', 'cat', 'monkey']], ... names=['type', 'name']) df limbs num_legs num_arms type name mammal dog 4 0 cat 4 0 monkey 2 2
df.rename_axis(index={'type': 'class'}) limbs num_legs num_arms class name mammal dog 4 0 cat 4 0 monkey 2 2
df.rename_axis(columns=str.upper) LIMBS num_legs num_arms type name mammal dog 4 0 cat 4 0 monkey 2 2