pull_requests: 288875953

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id node_id number state locked title user body created_at updated_at closed_at merged_at merge_commit_sha assignee milestone draft head base author_association auto_merge repo url merged_by
288875953 MDExOlB1bGxSZXF1ZXN0Mjg4ODc1OTUz 3028 closed 0 Add "errors" keyword argument to drop() and drop_dims() (#2994) 5852283 <!-- Feel free to remove check-list items aren't relevant to your change --> - [x] Closes #2994 - [x] Tests added - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API This addresses #2994 by adding an "errors" keyword argument to `Dataset.drop()`, `Dataset.drop_dims()`, and `DataArray.drop()`. I stuck with pandas' convention of using either `errors='raise'`, now the default that maintains previous behavior by raising an error if any passed label is not found in the dataset/array, or `errors='ignore'` in which case any missing labels are silently ignored. This seems like a pretty straightforward change; mainly it is just skipping checks for missing labels when `errors == 'ignore'` and passing the errors keyword over to the pandas method when using `index.drop()`. Hopefully there are no subtleties that I've missed. I added documentation to the appropriate methods, although I have been struggling to build the docs locally and am unsure if they look right. Also this is my first attempt to contribute to any project, so suggestions and feedback are welcome. 2019-06-17T14:34:19Z 2019-06-20T15:48:00Z 2019-06-20T15:48:00Z 2019-06-20T15:48:00Z 9c0bbf744a5235b4187f87de49175e6776d813cb     0 51a22fa4bcc0904de63966cce24314806f0d4462 c2a2a6efcaf2d279c78da4ba3a87ea96afe78be0 CONTRIBUTOR   13221727 https://github.com/pydata/xarray/pull/3028  

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