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DOC: Fixed the doctsring for _set_axis_name (GH 22895) #22969

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97 changes: 54 additions & 43 deletions pandas/core/generic.py
Original file line number Diff line number Diff line change
@@ -1154,29 +1154,32 @@ def rename_axis(self, mapper, axis=0, copy=True, inplace=False):
--------
**Series**

>>> s = pd.Series([1, 2, 3])
>>> s.rename_axis("foo")
foo
0 1
1 2
2 3
dtype: int64
>>> s = pd.Series(["dog", "cat", "monkey"])
>>> s.rename_axis("animal")
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animal
0 dog
1 cat
2 monkey
dtype: object

**DataFrame**

>>> df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
>>> df.rename_axis("foo")
A B
foo
0 1 4
1 2 5
2 3 6

>>> df.rename_axis("bar", axis="columns")
bar A B
0 1 4
1 2 5
2 3 6
>>> df = pd.DataFrame({"name": ["dog", "cat", "monkey"], "legs": [4, 4, 2]})
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this is longer than 79 characters, isn't it?

name legs
0 dog 4
1 cat 4
2 monkey 2
>>> df.rename_axis("animal")
name legs
animal
0 dog 4
1 cat 4
2 monkey 2
>>> df.rename_axis("id", axis="columns")
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In this case, the concept id refers to name and legs, which does not make sense.

It could make more sense to have the name as the index, and then may be a column num_legs and a column num_arms and call the axis limbs.

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Makes sense

id name legs
0 dog 4
1 cat 4
2 monkey 2
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
non_mapper = is_scalar(mapper) or (is_list_like(mapper) and not
@@ -1194,44 +1197,52 @@ def rename_axis(self, mapper, axis=0, copy=True, inplace=False):

def _set_axis_name(self, name, axis=0, inplace=False):
"""
Alter the name or names of the axis.
Alter the label(s) of the axis.
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This doesn't seem correct. Altering the labels would be changing the names of the columns, not the name of the axis itself.

And small thing, but alter doesn't necessarily need to be correct. If the axis doesn't have a name, it's setting it, but not altering. Set would be better I think.


Parameters
----------
name : str or list of str
Name for the Index, or list of names for the MultiIndex
axis : int or str
0 or 'index' for the index; 1 or 'columns' for the columns
inplace : bool
whether to modify `self` directly or return a copy
Labels(s) to set.
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Same as before, label is the names of each individual column, not the name of the axis

axis : {0 or 'index', 1 or 'columns'}, default 0
The axis to set the label. The value 0 or 'index' specifies index,
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and the value 1 or 'columns' specifies columns.
inplace : boolean, default False
If `True`, do operation inplace and return None.

.. versionadded:: 0.21.0

Returns
-------
renamed : same type as caller or None if inplace=True
Series, DataFrame, Panel, or None
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Can you remove Panel here. While it's correct, Panel it's already deprecated and will disappear in couple of months, so not worth having it.

The same type as the caller or `None` if `inplace` is `True`.

See Also
--------
pandas.DataFrame.rename
pandas.Series.rename
pandas.Index.rename
pandas.DataFrame.rename : Alter the labels of :class:`DataFrame`.
pandas.Series.rename : Alter the name or the labels :class:`Series`.
pandas.Index.rename : Alter the name of :class:`Index`
or :class:`MultiIndex`.

Examples
--------
>>> df._set_axis_name("foo")
A
foo
0 1
1 2
2 3
>>> df.index = pd.MultiIndex.from_product([['A'], ['a', 'b', 'c']])
>>> df._set_axis_name(["bar", "baz"])
A
bar baz
A a 1
b 2
c 3
>>> df = pd.DataFrame({"legs": [4, 4, 2]})
legs
0 4
1 4
2 2
>>> df._set_axis_name("animal")
legs
animal
0 4
1 2
2 0
>>> df.index = pd.MultiIndex.from_product([["mammal"], ['dog', 'cat', 'monkey']])
>>> df._set_axis_name(["type", "name"])
legs
type name
mammal dog 4
cat 4
monkey 2
"""
axis = self._get_axis_number(axis)
idx = self._get_axis(axis).set_names(name)