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