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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
342928718 MDExOlB1bGxSZXF1ZXN0MjAyNzE0MjUx 2302 WIP: lazy=True in apply_ufunc() shoyer 1217238 open 0     1 2018-07-20T00:01:21Z 2023-07-18T04:19:17Z   MEMBER   0 pydata/xarray/pulls/2302
  • [x] Closes https://github.com/pydata/xarray/issues/2298
  • [ ] Tests added
  • [ ] Tests passed
  • [ ] Fully documented, including whats-new.rst for all changes and api.rst for new API

Still needs more tests and documentation.

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    xarray 13221727 pull
895983112 MDExOlB1bGxSZXF1ZXN0NjQ4MTM1NTcy 5351 Add xarray.backends.NoMatchingEngineError shoyer 1217238 open 0     4 2021-05-19T22:09:21Z 2022-11-16T15:19:54Z   MEMBER   0 pydata/xarray/pulls/5351
  • [x] Closes #5329
  • [x] Tests added
  • [x] Passes pre-commit run --all-files
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [x] New functions/methods are listed in api.rst
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    xarray 13221727 pull
168272291 MDExOlB1bGxSZXF1ZXN0NzkzMjE2NTc= 924 WIP: progress toward making groupby work with multiple arguments shoyer 1217238 open 0     16 2016-07-29T08:07:57Z 2022-06-09T14:50:17Z   MEMBER   0 pydata/xarray/pulls/924

Fixes #324

It definitely doesn't work properly yet, totally mixing up coordinates, data variables and multi-indexes (as shown by the failing tests).

A simple example:

``` In [4]: coords = {'a': ('x', [0, 0, 1, 1]), 'b': ('y', [0, 0, 1, 1])}

In [5]: square = xr.DataArray(np.arange(16).reshape(4, 4), coords=coords, dims=['x', 'y'])

In [6]: square Out[6]: <xarray.DataArray (x: 4, y: 4)> array([[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11], [12, 13, 14, 15]]) Coordinates: b (y) int64 0 0 1 1 a (x) int64 0 0 1 1 * x (x) int64 0 1 2 3 * y (y) int64 0 1 2 3

In [7]: square.groupby(['a', 'b']).mean() Out[7]: <xarray.DataArray (a: 2, b: 2)> array([[ 2.5, 4.5], [ 10.5, 12.5]]) Coordinates: * a (a) int64 0 1 * b (b) int64 0 1

In [8]: square.groupby(['x', 'y']).mean() Out[8]: <xarray.DataArray (x: 4, y: 4)> array([[ 0., 1., 2., 3.], [ 4., 5., 6., 7.], [ 8., 9., 10., 11.], [ 12., 13., 14., 15.]]) Coordinates: * x (x) int64 0 1 2 3 * y (y) int64 0 1 2 3 ```

More examples: https://gist.github.com/shoyer/5cfa4d5751e8a78a14af25f8442ad8d5

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    xarray 13221727 pull

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