issue_comments: 554648042

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https://github.com/pydata/xarray/issues/3535#issuecomment-554648042 https://api.github.com/repos/pydata/xarray/issues/3535 554648042 MDEyOklzc3VlQ29tbWVudDU1NDY0ODA0Mg== 6628425 2019-11-16T15:39:23Z 2019-11-16T15:39:23Z MEMBER

Thanks for raising this issue @mathause. In hindsight this does not surprise me. Pandas's strict use of nanosecond-resolution datetimes and timedeltas was part of the motivation for the CFTimeIndex. While convenient, because it allows us to re-use code already written in pandas, holding the result of the difference between two CFTimeIndexes in a TimedeltaIndex clearly prevents us from taking the difference between distant dates.

Perhaps a more robust (yet more complex) solution for https://github.com/pydata/xarray/issues/2484 would be to write a version of a TimedeltaIndex that does not internally cast the timedeltas to type np.timedelta64[ns], and rather leaves them as datetime.timedelta objects, which are the actual result of subtracting two sequences of cftime.datetime objects.

Regarding the combine_by_coords issue, though, there might be an easier fix. Is there a reason that first_items is an Index of length-one Indexes? It's not clear to me why that needs to be the case.

https://github.com/pydata/xarray/blob/56c16e4bf45a3771fd9acba76d802c0199c14519/xarray/core/combine.py#L91

It appears if we just select the first value of each index (i.e. a cftime.datetime object in this example), e.g.

python first_items = pd.Index([index[0] for index in indexes]) pandas's rank method works properly and combine_by_coords produces the correct result:

```

xr.combine_by_coords([d1, d2, d3]).time <xarray.DataArray 'time' (time: 3)> array([cftime.DatetimeGregorian(4500, 12, 31, 0, 0, 0, 0, 4, 365), cftime.DatetimeGregorian(4600, 12, 31, 0, 0, 0, 0, 2, 365), cftime.DatetimeGregorian(5100, 12, 31, 0, 0, 0, 0, 0, 365)], dtype=object) Coordinates: * time (time) object 4500-12-31 00:00:00 ... 5100-12-31 00:00:00 ```

 
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