ordered=False, dtype='category')
        >>> idx.map({'a': 'first', 'b': 'second', 'c': 'third'})
        CategoricalIndex(['first', 'second', 'third'], categories=['first',
                         'second', 'third'], ordered=False, dtype='category')

        If the mapping is one-to-one the ordering of the categories is
        preserved:

        >>> idx = pd.CategoricalIndex(['a', 'b', 'c'], ordered=True)
        >>> idx
        CategoricalIndex(['a', 'b', 'c'], categories=['a', 'b', 'c'],
                         ordered=True, dtype='category')
        >>> idx.map({'a': 3, 'b': 2, 'c': 1})
        CategoricalIndex([3, 2, 1], categories=[3, 2, 1], ordered=True,
                         dtype='category')

        If the mapping is not one-to-one an :class:`~pandas.Index` is returned:

        >>> idx.map({'a': 'first', 'b': 'second', 'c': 'first'})
        Index(['first', 'second', 'first'], dtype='object')

        If a `dict` is used, all unmapped categories are mapped to `NaN` and
        the result is an :class:`~pandas.Index`:

        >>> idx.map({'a': 'first', 'b': 'second'})
        Index(['first', 'second', nan], dtype='object')
        )