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2 rows where repo = 13221727, type = "pull" and user = 13190237 sorted by updated_at descending

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  • pull · 2 ✖

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repo 1

  • xarray · 2 ✖
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
484212164 MDExOlB1bGxSZXF1ZXN0MzEwMTQwMTI2 3244 Make argmin/max work lazy with dask ulijh 13190237 closed 0     7 2019-08-22T20:55:49Z 2019-10-25T11:53:42Z 2019-09-06T23:15:19Z CONTRIBUTOR   0 pydata/xarray/pulls/3244

As @shoyer pointed out in https://github.com/pydata/xarray/issues/3237, nanargmax/min from numpy or dask should be used when not working on object arrays. Also, nanargmin/max were added to the nputils module so they should be using bottleneck if available.

  • [x] Closes #3237
  • [x] Tests added
  • [x] Passes black . && mypy . && flake8
  • [x] Fully documented, including whats-new.rst for all changes and api.rst for new API
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    xarray 13221727 pull
481110823 MDExOlB1bGxSZXF1ZXN0MzA3NjczNzgx 3221 Allow invalid_netcdf=True in to_netcdf() ulijh 13190237 closed 0     6 2019-08-15T11:32:56Z 2019-08-22T20:20:42Z 2019-08-22T20:12:11Z CONTRIBUTOR   0 pydata/xarray/pulls/3221

Hi all,

I prepared a little PR which could close #2243 and would allow for a IMO clean way of writing data with complex dtypes (and others).

What do you think?

TODOs:

  • [X] Closes #2243
  • [X] Tests added
  • [x] Passes black . && mypy . && flake8
  • [x] Fully documented, including whats-new.rst for all changes and api.rst for new API
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    xarray 13221727 pull

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