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Classe « Series »

Méthode pandas.Series.rename_axis

Signature de la méthode rename_axis

def rename_axis(self, mapper: 'IndexLabel | lib.NoDefault' = <no_default>, *, index=<no_default>, axis: 'Axis' = 0, copy: 'bool' = True, inplace: 'bool' = False) -> 'Self | None' 

Description

help(Series.rename_axis)

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.
    Note that the ``columns`` parameter is not allowed if the
    object is a Series. This parameter only apply for DataFrame
    type objects.

    Use either ``mapper`` and ``axis`` to
    specify the axis to target with ``mapper``, or ``index``
    and/or ``columns``.
axis : {0 or 'index', 1 or 'columns'}, default 0
    The axis to rename. For `Series` this parameter is unused and defaults to 0.
copy : bool, default None
    Also copy underlying data.

    .. note::
        The `copy` keyword will change behavior in pandas 3.0.
        `Copy-on-Write
        <https://pandas.pydata.org/docs/dev/user_guide/copy_on_write.html>`__
        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``
inplace : bool, default False
    Modifies the object directly, instead of creating a new Series
    or DataFrame.

Returns
-------
Series, DataFrame, or None
    The same type as the caller or None if ``inplace=True``.

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

* ``(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
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

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