html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/2481#issuecomment-699599921,https://api.github.com/repos/pydata/xarray/issues/2481,699599921,MDEyOklzc3VlQ29tbWVudDY5OTU5OTkyMQ==,26384082,2020-09-27T07:50:54Z,2020-09-27T07:50:54Z,NONE,"In order to maintain a list of currently relevant issues, we mark issues as stale after a period of inactivity
If this issue remains relevant, please comment here or remove the `stale` label; otherwise it will be marked as closed automatically
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,369639339
https://github.com/pydata/xarray/issues/2481#issuecomment-429856032,https://api.github.com/repos/pydata/xarray/issues/2481,429856032,MDEyOklzc3VlQ29tbWVudDQyOTg1NjAzMg==,81219,2018-10-15T13:39:25Z,2018-10-15T13:39:25Z,CONTRIBUTOR,"Got it, thanks for the workaround !
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,369639339
https://github.com/pydata/xarray/issues/2481#issuecomment-429497014,https://api.github.com/repos/pydata/xarray/issues/2481,429497014,MDEyOklzc3VlQ29tbWVudDQyOTQ5NzAxNA==,6628425,2018-10-13T00:42:35Z,2018-10-13T00:42:35Z,MEMBER,"I think this would be a fair amount of work to implement :), but in principle it would be a natural step forward in the pattern we have been following in porting time series functionality from pandas for use with calendars supported by `cftime`.
In the short term, at least for the use-case you describe above, I think a potentially simpler option would be to use a call to `CFTimeIndex.shift`; based on your example I'll illustrate with the DatetimeIndex version, since `resample` doesn't exist yet for a CFTimeIndex:
```
In [1]: import xarray as xr; import pandas as pd
In [2]: times = pd.date_range('2000', periods=361)
In [3]: da = xr.DataArray(range(361), [('time', times)])
In [4]: monthly_count = da.resample(time='M').count()
In [5]: end_time = monthly_count.indexes['time']
In [6]: start_time = end_time.shift(-1, 'M')
In [7]: expected_days_in_group = end_time - start_time
In [8]: expected_days_in_group
Out[8]:
TimedeltaIndex(['31 days', '29 days', '31 days', '30 days', '31 days',
'30 days', '31 days', '31 days', '30 days', '31 days',
'30 days', '31 days'],
dtype='timedelta64[ns]', name=u'time', freq=None)
```
Note that currently subtracting one CFTimeIndex from another (analogous to `end_time - start_time` in the example above) raises an error (I think it should also return a TimedeltaIndex), but that's probably a straightforward fix (I'll create a separate issue):
```
In [8]: a = xr.cftime_range('2000', periods=12, freq='M')
In [9]: b = a.shift(-1, 'M')
In [10]: a - b
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
in ()
----> 1 a - b
/Users/spencerclark/xarray-dev/xarray/xarray/coding/cftimeindex.pyc in __sub__(self, other)
365
366 def __sub__(self, other):
--> 367 return CFTimeIndex(np.array(self) - other)
368
369
TypeError: unsupported operand type(s) for -: 'numpy.ndarray' and 'CFTimeIndex'
```
-----
As a side note, support even for standard PeriodIndexes in xarray needs some work -- see the following existing open issues: #1270, #1565. Serialization to netCDF files would also be nice to support (but I don't see an existing issue for that). I'm sure work to fix these issues would also be appreciated!","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,369639339