@@ -984,117 +984,8 @@ def _rename(
984984 level : Level | None = None ,
985985 errors : str = "ignore" ,
986986 ) -> NDFrameT | None :
987- """
988- Alter axes input function or functions. Function / dict values must be
989- unique (1-to-1). Labels not contained in a dict / Series will be left
990- as-is. Extra labels listed don't throw an error. Alternatively, change
991- ``Series.name`` with a scalar value (Series only).
992-
993- Parameters
994- ----------
995- %(axes)s : scalar, list-like, dict-like or function, optional
996- Scalar or list-like will alter the ``Series.name`` attribute,
997- and raise on DataFrame.
998- dict-like or functions are transformations to apply to
999- that axis' values
1000- copy : bool, default True
1001- Also copy underlying data.
1002- inplace : bool, default False
1003- Whether to return a new {klass}. If True then value of copy is
1004- ignored.
1005- level : int or level name, default None
1006- In case of a MultiIndex, only rename labels in the specified
1007- level.
1008- errors : {'ignore', 'raise'}, default 'ignore'
1009- If 'raise', raise a `KeyError` when a dict-like `mapper`, `index`,
1010- or `columns` contains labels that are not present in the Index
1011- being transformed.
1012- If 'ignore', existing keys will be renamed and extra keys will be
1013- ignored.
1014-
1015- Returns
1016- -------
1017- renamed : {klass} (new object)
1018-
1019- Raises
1020- ------
1021- KeyError
1022- If any of the labels is not found in the selected axis and
1023- "errors='raise'".
987+ # called by Series.rename and DataFrame.rename
1024988
1025- See Also
1026- --------
1027- NDFrame.rename_axis
1028-
1029- Examples
1030- --------
1031- >>> s = pd.Series([1, 2, 3])
1032- >>> s
1033- 0 1
1034- 1 2
1035- 2 3
1036- dtype: int64
1037- >>> s.rename("my_name") # scalar, changes Series.name
1038- 0 1
1039- 1 2
1040- 2 3
1041- Name: my_name, dtype: int64
1042- >>> s.rename(lambda x: x ** 2) # function, changes labels
1043- 0 1
1044- 1 2
1045- 4 3
1046- dtype: int64
1047- >>> s.rename({1: 3, 2: 5}) # mapping, changes labels
1048- 0 1
1049- 3 2
1050- 5 3
1051- dtype: int64
1052-
1053- Since ``DataFrame`` doesn't have a ``.name`` attribute,
1054- only mapping-type arguments are allowed.
1055-
1056- >>> df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
1057- >>> df.rename(2)
1058- Traceback (most recent call last):
1059- ...
1060- TypeError: 'int' object is not callable
1061-
1062- ``DataFrame.rename`` supports two calling conventions
1063-
1064- * ``(index=index_mapper, columns=columns_mapper, ...)``
1065- * ``(mapper, axis={'index', 'columns'}, ...)``
1066-
1067- We *highly* recommend using keyword arguments to clarify your
1068- intent.
1069-
1070- >>> df.rename(index=str, columns={"A": "a", "B": "c"})
1071- a c
1072- 0 1 4
1073- 1 2 5
1074- 2 3 6
1075-
1076- >>> df.rename(index=str, columns={"A": "a", "C": "c"})
1077- a B
1078- 0 1 4
1079- 1 2 5
1080- 2 3 6
1081-
1082- Using axis-style parameters
1083-
1084- >>> df.rename(str.lower, axis='columns')
1085- a b
1086- 0 1 4
1087- 1 2 5
1088- 2 3 6
1089-
1090- >>> df.rename({1: 2, 2: 4}, axis='index')
1091- A B
1092- 0 1 4
1093- 2 2 5
1094- 4 3 6
1095-
1096- See the :ref:`user guide <basics.rename>` for more.
1097- """
1098989 if mapper is None and index is None and columns is None :
1099990 raise TypeError ("must pass an index to rename" )
1100991
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