Meant to reproduce the results of the following

        grouper = pandas.Grouper(...)
        first_items = pd.Series(np.arange(len(index)),
                                index).groupby(grouper).first()

        with index being a CFTimeIndex instead of a DatetimeIndex.

def first_items(self, index):
        """Meant to reproduce the results of the following

        grouper = pandas.Grouper(...)
        first_items = pd.Series(np.arange(len(index)),
                                index).groupby(grouper).first()

        with index being a CFTimeIndex instead of a DatetimeIndex.
        """

        datetime_bins, labels = _get_time_bins(index, self.freq, self.closed,
                                               self.label, self.base)
        if self.loffset is not None:
            if isinstance(self.loffset, datetime.timedelta):
                labels = labels + self.loffset
            else:
                labels = labels + to_offset(self.loffset)

        # check binner fits data
        if index[0] < datetime_bins[0]:
            raise ValueError("Value falls before first bin")
        if index[-1] > datetime_bins[-1]:
            raise ValueError("Value falls after last bin")

        integer_bins = np.searchsorted(
            index, datetime_bins, side=self.closed)[:-1]
        first_items = pd.Series(integer_bins, labels)

        # Mask duplicate values with NaNs, preserving the last values
        non_duplicate = ~first_items.duplicated('last')
        return first_items.where(non_duplicate)