issue_comments

Take a look at https://github.com/pydata/xarray/pull/2458 for a very basic version of this.

Yes, that would probably be a good idea. On Thu, Jun 21, 2018 at 9:51 PM Aidan Heerdegen notifications@github.com wrote:

Does this need it's own issue then, so it doesn't get lost?

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shift() is different from resampling, but indeed it looks like we’ll need to add it manually to CFTimeIndex. On Thu, Jun 21, 2018 at 9:12 PM Aidan Heerdegen notifications@github.com wrote:

I'm not sure if my issue belongs in here, but I didn't want to create a new Issue (there are already 455 open ones).

I am experimenting with the new CFTimeIndex functionality (thanks heaps BTW! That was a mammoth effort if the PR thread is anything to go by).

I am trying to shift a time index as I need to align datasets to a common start point. So using the example code above,

da.time.get_index('time').shift(1,'D')---------------------------------------------------------------------------NotImplementedError Traceback (most recent call last)<ipython-input-71-db48b2fbb340> in <module>()----> 1 da.time.get_index('time').shift(1,'D') /g/data3/hh5/public/apps/miniconda3/envs/analysis27-18.04/lib/python2.7/site-packages/pandas/core/indexes/base.pyc in shift(self, periods, freq) 2627 """ 2628 raise NotImplementedError("Not supported for type %s" %-> 2629 type(self).name) 2630 2631 def argsort(self, args, *kwargs):NotImplementedError: Not supported for type CFTimeIndex

Is this not implemented because it might require resampling?

I ask because this works:

times[0] + pd.Timedelta('365 days') cftime.DatetimeNoLeap(2, 1, 1, 0, 0, 0, 0, -1, 1)```

I guess I am asking, if I want to shift a time index is the best (only?) way currently to loop over all the individual elements of the index and add a time offset to each?

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Yes, I think so. The main thing we need is a function to map from datetime -> datetime at start of frequency.