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  • shoyer · 2 ✖

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  • Convert an existing xarray dimension into a MultiIndex · 2 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
289856794 https://github.com/pydata/xarray/issues/1331#issuecomment-289856794 https://api.github.com/repos/pydata/xarray/issues/1331 MDEyOklzc3VlQ29tbWVudDI4OTg1Njc5NA== shoyer 1217238 2017-03-28T18:11:02Z 2017-03-28T18:11:02Z MEMBER

Given your two Datasets and your desired result, why not simply using concat?

OK, I feel pretty dumb now. Yes, that's totally the right way to do this. For some reason I was fixated on converting each dataset individually to have a MultiIndex before combining them.

 
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   Convert an existing xarray dimension into a MultiIndex 217347106
289559117 https://github.com/pydata/xarray/issues/1331#issuecomment-289559117 https://api.github.com/repos/pydata/xarray/issues/1331 MDEyOklzc3VlQ29tbWVudDI4OTU1OTExNw== shoyer 1217238 2017-03-27T19:27:27Z 2017-03-27T19:27:27Z MEMBER

Currently the best I have is: python (ds1.reset_index('x') .rename({'x': 'yx', 'x_': 'x'}) .assign_coords(y=lambda ds: (('yx',), [ds.y.item()] * 3)) .set_index(yx=['y', 'x'])) <xarray.Dataset> Dimensions: (yx: 3) Coordinates: * yx (yx) MultiIndex - y (yx) object 'a' 'a' 'a' - x (yx) int64 1 2 3 Data variables: foo (yx) int64 1 2 3 which is rather un-intuitive.

It occurs to me that maybe this is just a good use case for expand_dims (#1326), which could make this as simple as ds1.expand_dims('y').stack(yx=['y', 'x']))

 
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   Convert an existing xarray dimension into a MultiIndex 217347106

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