issue_comments: 822098673

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https://github.com/pydata/xarray/pull/5089#issuecomment-822098673 https://api.github.com/repos/pydata/xarray/issues/5089 822098673 MDEyOklzc3VlQ29tbWVudDgyMjA5ODY3Mw== 5635139 2021-04-19T00:41:47Z 2021-04-19T00:41:47Z MEMBER

@max-sixty is there a case where you don't think we could do a single isel? I'd love to do the single isel() call if possible, because that should have the best performance by far.

IIUC there are two broad cases here - where every supplied coord is a dimensioned coord — it's v simple, just isel non-duplicates for each dimension* - where there's a non-dimensioned coord with ndim > 1, then it requires stacking; e.g. the example above. Is there a different way of doing this?

```python In [12]: da Out[12]: <xarray.DataArray (init: 2, tau: 3)> array([[1, 2, 3], [4, 5, 6]]) Coordinates: * init (init) int64 0 1 * tau (tau) int64 1 2 3 valid (init, tau) int64 8 6 6 7 7 7

In [13]: da.drop_duplicate_coords("valid") Out[13]: <xarray.DataArray (valid: 3)> array([1, 2, 4]) Coordinates: * valid (valid) int64 8 6 7 init (valid) int64 0 0 1 tau (valid) int64 1 2 1 ```

* very close to this is a 1D non-dimensioned coord, in which case we can either turn it into a dimensioned coord or retain the existing dimensioned coords — I think probably the former if we allow the stacking case, for the sake of consistency.

 
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