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DOC: Fixed the doctsring for _set_axis_name (GH 22895) (pandas-dev#22969)
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‎pandas/core/generic.py

+110-94
Original file line numberDiff line numberDiff line change
@@ -1109,35 +1109,41 @@ def rename(self, *args, **kwargs):
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('inplace', False)])
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def rename_axis(self, mapper=None, **kwargs):
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"""
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Alter the name of the index or name of Index object that is the
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columns.
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Set the name of the axis for the index or columns.
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Parameters
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----------
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mapper : scalar, list-like, optional
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Value to set the axis name attribute.
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index, columns : scalar, list-like, dict-like or function, optional
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dict-like or functions transformations to apply to
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that axis' values.
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A scalar, list-like, dict-like or functions transformations to
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apply to that axis' values.
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Use either ``mapper`` and ``axis`` to
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specify the axis to target with ``mapper``, or ``index``
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and/or ``columns``.
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.. versionchanged:: 0.24.0
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axis : int or string, default 0
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copy : boolean, default True
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axis : {0 or 'index', 1 or 'columns'}, default 0
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The axis to rename.
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copy : bool, default True
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Also copy underlying data.
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inplace : boolean, default False
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inplace : bool, default False
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Modifies the object directly, instead of creating a new Series
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or DataFrame.
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Returns
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-------
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renamed : Series, DataFrame, or None
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Series, DataFrame, or None
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The same type as the caller or None if `inplace` is True.
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See Also
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--------
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Series.rename : Alter Series index labels or name.
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DataFrame.rename : Alter DataFrame index labels or name.
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Index.rename : Set new names on index.
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Notes
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-----
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Prior to version 0.21.0, ``rename_axis`` could also be used to change
@@ -1162,75 +1168,73 @@ def rename_axis(self, mapper=None, **kwargs):
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We *highly* recommend using keyword arguments to clarify your
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intent.
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See Also
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--------
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Series.rename : Alter Series index labels or name.
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DataFrame.rename : Alter DataFrame index labels or name.
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Index.rename : Set new names on index.
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Examples
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--------
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**Series**
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>>> s = pd.Series([1, 2, 3])
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>>> s.rename_axis("foo")
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foo
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0 1
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1 2
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2 3
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dtype: int64
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>>> s = pd.Series(["dog", "cat", "monkey"])
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>>> s
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0 dog
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1 cat
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2 monkey
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dtype: object
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>>> s.rename_axis("animal")
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animal
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0 dog
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1 cat
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2 monkey
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dtype: object
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**DataFrame**
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>>> df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
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>>> df.rename_axis("foo")
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A B
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foo
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0 1 4
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1 2 5
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2 3 6
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>>> df.rename_axis("bar", axis="columns")
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bar A B
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0 1 4
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1 2 5
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2 3 6
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>>> mi = pd.MultiIndex.from_product([['a', 'b', 'c'], [1, 2]],
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... names=['let','num'])
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>>> df = pd.DataFrame({'x': [i for i in range(len(mi))],
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... 'y' : [i*10 for i in range(len(mi))]},
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... index=mi)
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>>> df.rename_axis(index={'num' : 'n'})
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x y
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let n
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a 1 0 0
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2 1 10
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b 1 2 20
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2 3 30
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c 1 4 40
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2 5 50
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>>> cdf = df.rename_axis(columns='col')
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>>> cdf
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col x y
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let num
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a 1 0 0
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2 1 10
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b 1 2 20
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2 3 30
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c 1 4 40
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2 5 50
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>>> cdf.rename_axis(columns=str.upper)
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COL x y
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let num
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a 1 0 0
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2 1 10
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b 1 2 20
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2 3 30
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c 1 4 40
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2 5 50
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>>> df = pd.DataFrame({"num_legs": [4, 4, 2],
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... "num_arms": [0, 0, 2]},
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... ["dog", "cat", "monkey"])
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>>> df
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num_legs num_arms
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dog 4 0
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cat 4 0
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monkey 2 2
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>>> df = df.rename_axis("animal")
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>>> df
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num_legs num_arms
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animal
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dog 4 0
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cat 4 0
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monkey 2 2
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>>> df = df.rename_axis("limbs", axis="columns")
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>>> df
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limbs num_legs num_arms
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animal
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dog 4 0
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cat 4 0
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monkey 2 2
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**MultiIndex**
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>>> df.index = pd.MultiIndex.from_product([['mammal'],
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... ['dog', 'cat', 'monkey']],
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... names=['type', 'name'])
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>>> df
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limbs num_legs num_arms
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type name
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mammal dog 4 0
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cat 4 0
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monkey 2 2
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>>> df.rename_axis(index={'type': 'class'})
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limbs num_legs num_arms
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class name
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mammal dog 4 0
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cat 4 0
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monkey 2 2
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>>> df.rename_axis(columns=str.upper)
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LIMBS num_legs num_arms
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type name
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mammal dog 4 0
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cat 4 0
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monkey 2 2
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"""
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axes, kwargs = self._construct_axes_from_arguments((), kwargs)
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copy = kwargs.pop('copy', True)
@@ -1285,45 +1289,57 @@ def rename_axis(self, mapper=None, **kwargs):
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def _set_axis_name(self, name, axis=0, inplace=False):
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"""
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Alter the name or names of the axis.
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Set the name(s) of the axis.
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Parameters
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----------
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name : str or list of str
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Name for the Index, or list of names for the MultiIndex
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axis : int or str
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0 or 'index' for the index; 1 or 'columns' for the columns
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inplace : bool
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whether to modify `self` directly or return a copy
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Name(s) to set.
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axis : {0 or 'index', 1 or 'columns'}, default 0
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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.
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inplace : bool, default False
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If `True`, do operation inplace and return None.
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.. versionadded:: 0.21.0
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Returns
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-------
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renamed : same type as caller or None if inplace=True
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Series, DataFrame, or None
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The same type as the caller or `None` if `inplace` is `True`.
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See Also
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--------
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pandas.DataFrame.rename
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pandas.Series.rename
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pandas.Index.rename
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DataFrame.rename : Alter the axis labels of :class:`DataFrame`.
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Series.rename : Alter the index labels or set the index name
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of :class:`Series`.
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Index.rename : Set the name of :class:`Index` or :class:`MultiIndex`.
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Examples
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--------
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>>> df._set_axis_name("foo")
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A
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foo
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0 1
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1 2
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2 3
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>>> df.index = pd.MultiIndex.from_product([['A'], ['a', 'b', 'c']])
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>>> df._set_axis_name(["bar", "baz"])
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A
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bar baz
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A a 1
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b 2
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c 3
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"""
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>>> df = pd.DataFrame({"num_legs": [4, 4, 2]},
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... ["dog", "cat", "monkey"])
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>>> df
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num_legs
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dog 4
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cat 4
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monkey 2
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>>> df._set_axis_name("animal")
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num_legs
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animal
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dog 4
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cat 4
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monkey 2
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>>> df.index = pd.MultiIndex.from_product(
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... [["mammal"], ['dog', 'cat', 'monkey']])
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>>> df._set_axis_name(["type", "name"])
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legs
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type name
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mammal dog 4
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cat 4
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monkey 2
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"""
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pd.MultiIndex.from_product([["mammal"], ['dog', 'cat', 'monkey']])
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axis = self._get_axis_number(axis)
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idx = self._get_axis(axis).set_names(name)
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