def _to_multi_series(self, series: pd.DataFrame) -> list[TimeSeries]:
        """
        load the Uber TLC dataset as a list of univariate timeseries, one for each locationID.
        """

        ts_list = []  # list of timeseries
        for label in _build_tqdm_iterator(
            series, verbose=True, total=len(series.columns)
        ):
            srs = series[label]

            # filter column down to the period of recording
            start_date = min(srs.ffill().dropna().index)
            end_date = max(srs.bfill().dropna().index)
            active_range = (srs.index >= start_date) & (srs.index <= end_date)
            srs = srs[active_range]

            # convert to timeseries
            tmp = pd.DataFrame({"locationID": srs})
            tmp["date"] = tmp.index
            ts = TimeSeries.from_dataframe(tmp, "date", ["locationID"])
            ts_list.append(ts)
        return ts_list

        load the Uber TLC dataset as a list of univariate timeseries, one for each locationID.
        
darts/datasets/__init__.py