Classe « DataFrame »

Méthode pandas.DataFrame.rename

Signature de la méthode rename

def rename(self, mapper=None, index=None, columns=None, axis=None, copy=True, inplace=False, level=None, errors='ignore') 

Description

rename.__doc__

        Alter axes labels.

        Function / dict values must be unique (1-to-1). Labels not contained in
        a dict / Series will be left as-is. Extra labels listed don't throw an
        error.

        See the :ref:`user guide <basics.rename>` for more.

        Parameters
        ----------
        mapper : dict-like or function
            Dict-like or function transformations to apply to
            that axis' values. Use either ``mapper`` and ``axis`` to
            specify the axis to target with ``mapper``, or ``index`` and
            ``columns``.
        index : dict-like or function
            Alternative to specifying axis (``mapper, axis=0``
            is equivalent to ``index=mapper``).
        columns : dict-like or function
            Alternative to specifying axis (``mapper, axis=1``
            is equivalent to ``columns=mapper``).
        axis : {0 or 'index', 1 or 'columns'}, default 0
            Axis to target with ``mapper``. Can be either the axis name
            ('index', 'columns') or number (0, 1). The default is 'index'.
        copy : bool, default True
            Also copy underlying data.
        inplace : bool, default False
            Whether to return a new DataFrame. If True then value of copy is
            ignored.
        level : int or level name, default None
            In case of a MultiIndex, only rename labels in the specified
            level.
        errors : {'ignore', 'raise'}, default 'ignore'
            If 'raise', raise a `KeyError` when a dict-like `mapper`, `index`,
            or `columns` contains labels that are not present in the Index
            being transformed.
            If 'ignore', existing keys will be renamed and extra keys will be
            ignored.

        Returns
        -------
        DataFrame or None
            DataFrame with the renamed axis labels or None if ``inplace=True``.

        Raises
        ------
        KeyError
            If any of the labels is not found in the selected axis and
            "errors='raise'".

        See Also
        --------
        DataFrame.rename_axis : Set the name of the axis.

        Examples
        --------
        ``DataFrame.rename`` supports two calling conventions

        * ``(index=index_mapper, columns=columns_mapper, ...)``
        * ``(mapper, axis={'index', 'columns'}, ...)``

        We *highly* recommend using keyword arguments to clarify your
        intent.

        Rename columns using a mapping:

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

        Rename index using a mapping:

        >>> df.rename(index={0: "x", 1: "y", 2: "z"})
           A  B
        x  1  4
        y  2  5
        z  3  6

        Cast index labels to a different type:

        >>> df.index
        RangeIndex(start=0, stop=3, step=1)
        >>> df.rename(index=str).index
        Index(['0', '1', '2'], dtype='object')

        >>> df.rename(columns={"A": "a", "B": "b", "C": "c"}, errors="raise")
        Traceback (most recent call last):
        KeyError: ['C'] not found in axis

        Using axis-style parameters:

        >>> df.rename(str.lower, axis='columns')
           a  b
        0  1  4
        1  2  5
        2  3  6

        >>> df.rename({1: 2, 2: 4}, axis='index')
           A  B
        0  1  4
        2  2  5
        4  3  6