issues: 205473898

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
205473898 MDExOlB1bGxSZXF1ZXN0MTA0NzI2NzIz 1252 CFTimeIndex 6628425 closed 0     70 2017-02-06T02:10:47Z 2019-02-18T20:54:03Z 2018-05-13T05:19:11Z MEMBER   0 pydata/xarray/pulls/1252
  • [x] closes #1084
  • [x] passes git diff upstream/master | flake8 --diff
  • [x] tests added / passed
  • [x] whatsnew entry

This work in progress PR is a start on implementing a NetCDFTimeIndex, a subclass of pandas.Index, which closely mimics pandas.DatetimeIndex, but uses netcdftime._netcdftime.datetime objects. Currently implemented in the new index are: - Partial datetime-string indexing (using strictly ISO8601-format strings, using a date parser implemented by @shoyer in https://github.com/pydata/xarray/issues/1084#issuecomment-274372547) - Field-accessors for year, month, day, hour, minute, second, and microsecond, to enable groupby operations on attributes of date objects

This index is meant as a step towards improving the handling of non-standard calendars and dates outside the range Timestamp('1677-09-21 00:12:43.145225') to Timestamp('2262-04-11 23:47:16.854775807').

For now I have pushed only the code and some tests for the new index; I want to make sure the index is solid and well-tested before we consider integrating it into any of xarray's existing logic or writing any documentation.

Regarding the index, there are a couple remaining outstanding issues (that at least I'm aware of):

  1. Currently one can create non-sensical datetimes using netcdftime._netcdftime.datetime objects. This means one can attempt to index with an out-of-bounds string or datetime without raising an error. Could this possibly be addressed upstream? For example: ``` In [1]: from netcdftime import DatetimeNoLeap

In [2]: DatetimeNoLeap(2000, 45, 45) Out[2]: netcdftime._netcdftime.DatetimeNoLeap(2000, 45, 45, 0, 0, 0, 0, -1, 1) 2. I am looking to enable this index to be used in pandas.Series and pandas.DataFrame objects as well; this requires implementing aget_valuemethod. I have taken @shoyer's suggested simplified approach from https://github.com/pydata/xarray/issues/1084#issuecomment-275963433, and tweaked it to also allow for slice indexing, so I think this is most of the way there. A remaining to-do for me, however, is to implement something to allow for integer-indexing outside ofiloc, e.g. if you have a pandas.Seriesseries, indexing with the syntaxseries[1]orseries[1:3]```.

Hopefully this is a decent start; in particular I'm not an expert in writing tests so please let me know if there are improvements I can make to the structure and / or style I've used so far. I'm happy to make changes. I appreciate your help.

 
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