issue_comments: 312998916

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https://github.com/pydata/xarray/pull/1469#issuecomment-312998916 https://api.github.com/repos/pydata/xarray/issues/1469 312998916 MDEyOklzc3VlQ29tbWVudDMxMjk5ODkxNg== 1217238 2017-07-05T05:21:45Z 2017-07-05T05:21:45Z MEMBER

OK, I think I finally understand the nuance of the return value -- thanks for describing that fully for me.

In theory (after #974 is implemented), the current return value from indexes_min should work for indexing, e.g., ```

indexes = da.indexes_min(dims='y') indexes <xarray.Dataset> Dimensions: (x: 3) Coordinates: * x (x) <U1 'c' 'b' 'a' Data variables: y (x) int64 0 1 0

da.sel(x=indexes.x, y=indexes.y) # or ds.sel(**indexes) <xarray.DataArray (x: 3)> array([ 1, 40, 5]) Coordinates: * x (x) <U1 'c' 'b' 'a' ``` So maybe that is the right choice, though I'm not entirely certain yet.

Side note: I'm still not super happy with the names idxmin and indexes_min. They look too different for methods that are only a small variation on each other. Maybe idxmin_dataset or idxmin_dict?

 
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