我正在嘗試將xarray數(shù)據(jù)數(shù)組轉換為機器學習項目的 pandas 數(shù)據(jù)幀，但時間數(shù)據(jù)似乎采用一種cftime.DatetimeJulian格式，使用 pandasto_datetime()方法無法轉換。建議？謝謝。nor_xr.time<xarray.DataArray 'time' (time: 1372)>array([cftime.DatetimeJulian(2015, 3, 31, 0, 0, 0, 0, 0, 90),       cftime.DatetimeJulian(2018, 12, 31, 0, 0, 0, 0, 6, 365)], dtype=object)Coordinates:  * time     (time) object 2015-03-31 00:00:00 ... 2018-12-31 00:00:00Attributes:    standard_name:  time    axis:           Tnor_df = nor_xr.to_dataframe().reset_index()nor_df.head()    time0   2015-03-31 00:00:001   2015-04-01 00:00:00pd.to_datetime(nor_df.time)---------------------------------------------------------------------------TypeError                                 Traceback (most recent call last)<ipython-input-104-1f0fc00ad825> in <module>      2       3 #|nor_df.time.unique()----> 4 pd.to_datetime(nor_df.time)~\AppData\Local\Continuum\anaconda3A\lib\site-packages\pandas\core\tools\datetimes.py in to_datetime(arg, errors, dayfirst, yearfirst, utc, box, format, exact, unit, infer_datetime_format, origin, cache)    449         else:    450             from pandas import Series--> 451             values = _convert_listlike(arg._values, True, format)    452             result = Series(values, index=arg.index, name=arg.name)    453     elif isinstance(arg, (ABCDataFrame, MutableMapping)):~\AppData\Local\Continuum\anaconda3A\lib\site-packages\pandas\core\tools\datetimes.py in _convert_listlike(arg, box, format, name, tz)    366                     dayfirst=dayfirst,    367                     yearfirst=yearfirst,--> 368                     require_iso8601=require_iso8601    369                 )    370 pandas\_libs\tslib.pyx in pandas._libs.tslib.array_to_datetime()pandas\_libs\tslib.pyx in pandas._libs.tslib.array_to_datetime()pandas\_libs\tslib.pyx in pandas._libs.tslib.array_to_datetime()TypeError: <class 'cftime._cftime.DatetimeJulian'> is not convertible to datetime