pull_requests: 209931263

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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
209931263 MDExOlB1bGxSZXF1ZXN0MjA5OTMxMjYz 2375 closed 0 Make `dim` optional on unstack 4806877 - [x] Tests added (for all bug fixes or enhancements) - [x] Tests passed (for all non-documentation changes) - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later) Not sure if this is a desirable change but I thought it could be easily discussed as a PR. Just for context I was looking at flattening spatial data for machine learning pipelines and then reshaping after the output had been acquired. I have a NxM array called `b` and am flattening it like: ```python flat_input = b.stack(z=('y', 'x')) ``` Then I use that flat_input in my ML pipeline and get back an `np.array` (called `output`) which I want to unstack using all the metadata that went into stacking my original NxM array b. ```python xr.full_like(flat_input, output).unstack(dim='z') ``` This PR just makes the `dim` argument optional in unstack so that we can use ```python xr.full_like(flat_input, output).unstack() ``` As a follow on PR I was thinking of making a function called `xr.unstack_like(other: xr.DataArray|xr.Dataset, data: array_like)` to encompass this functionality. A couple questions: 1) Would something like `xr.unstack_like` be desirable? 2) Should we be using `xr.full_like` in this way? The documentation in xarray and numpy only mentions scalars, but arrays work fine in both. If this is a supported behavior I could add docs, and if not perhaps a copy and overwrite is a better approach? Here is a gist of the workflow using a tweaked datashader example and datashader example data https://gist.github.com/jsignell/79a6cf2da5c1458211d9dcf34d4417df 2018-08-21T19:29:06Z 2018-09-05T16:01:23Z 2018-09-05T15:19:07Z 2018-09-05T15:19:07Z 73f5b02a42a4003815d2bfc91e658195f5050be1     0 7ec32529652c9b19b18e747154a31b20d2c57b6e 69086b332c6c950587830b266df4e624c2106d89 CONTRIBUTOR   13221727 https://github.com/pydata/xarray/pull/2375  

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