issues: 456971151

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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
456971151 MDExOlB1bGxSZXF1ZXN0Mjg4ODc1OTUz 3028 Add "errors" keyword argument to drop() and drop_dims() (#2994) 5852283 closed 0     5 2019-06-17T14:34:19Z 2019-06-20T15:48:00Z 2019-06-20T15:48:00Z CONTRIBUTOR   0 pydata/xarray/pulls/3028
  • [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. 

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