    >>> ser.searchsorted([0, 4])
        array([0, 3])

        >>> ser.searchsorted([1, 3], side='left')
        array([0, 2])

        >>> ser.searchsorted([1, 3], side='right')
        array([1, 3])

        >>> ser = pd.Series(pd.to_datetime(['3/11/2000', '3/12/2000', '3/13/2000']))
        >>> ser
        0   2000-03-11
        1   2000-03-12
        2   2000-03-13
        dtype: datetime64[ns]

        >>> ser.searchsorted('3/14/2000')
        3

        >>> ser = pd.Categorical(
        ...     ['apple', 'bread', 'bread', 'cheese', 'milk'], ordered=True
        ... )
        >>> ser
        ['apple', 'bread', 'bread', 'cheese', 'milk']
        Categories (4, object): ['apple' < 'bread' < 'cheese' < 'milk']

        >>> ser.searchsorted('bread')
        1

        >>> ser.searchsorted(['bread'], side='right')
        array([3])

        If the values are not monotonically sorted, wrong locations
        may be returned:

        >>> ser = pd.Series([2, 1, 3])
        >>> ser
        0    2
        1    1
        2    3
        dtype: int64

        >>> ser.searchsorted(1)  # doctest: +SKIP
        0  # wrong result, correct would be 1
        