DataFrame.
rename_axis
Set the name of the axis for the index or columns.
mapper (scalar, list-like, optional) – Value to set the axis name attribute.
index (scalar, list-like, dict-like or function, optional) –
A scalar, list-like, dict-like or functions transformations to apply to that axis’ values. Note that the columns parameter is not allowed if the object is a Series. This parameter only apply for DataFrame type objects.
columns
Use either mapper and axis to specify the axis to target with mapper, or index and/or columns.
mapper
axis
index
columns (scalar, list-like, dict-like or function, optional) –
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.
The same type as the caller or None if inplace is True.
Series, DataFrame, or None
See also
Series.rename
Alter Series index labels or name.
DataFrame.rename
Alter DataFrame index labels or name.
Index.rename
Set new names on index.
Notes
DataFrame.rename_axis supports two calling conventions
DataFrame.rename_axis
(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.
copy
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
>>> import mars.dataframe as md >>> s = md.Series(["dog", "cat", "monkey"]) >>> s.execute() 0 dog 1 cat 2 monkey dtype: object >>> s.rename_axis("animal").execute() animal 0 dog 1 cat 2 monkey dtype: object
DataFrame
>>> df = md.DataFrame({"num_legs": [4, 4, 2], ... "num_arms": [0, 0, 2]}, ... ["dog", "cat", "monkey"]) >>> df.execute() num_legs num_arms dog 4 0 cat 4 0 monkey 2 2 >>> df = df.rename_axis("animal") >>> df.execute() num_legs num_arms animal dog 4 0 cat 4 0 monkey 2 2 >>> df = df.rename_axis("limbs", axis="columns") >>> df.execute() limbs num_legs num_arms animal dog 4 0 cat 4 0 monkey 2 2