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  • dcherian · 2 ✖

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  • Pass indexes directly to the DataArray and Dataset constructors · 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
1295217001 https://github.com/pydata/xarray/pull/7214#issuecomment-1295217001 https://api.github.com/repos/pydata/xarray/issues/7214 IC_kwDOAMm_X85NM3Fp dcherian 2448579 2022-10-28T16:41:19Z 2022-10-28T16:41:36Z MEMBER

t would be adding another pandas.MultiIndex special case while we'd like to remove them in Xarray.

True, but its neatly encapsulated in one place. And if we are going to support many Index classes that build on numpy, scipy, then support for pandas indexes seems entirely in-scope.

I'd just want to add that, from my experience with debugging multi-index issues, it is hard even for advanced users to see what's going wrong when coordinates and indexes are not consistent.

Should we expose xr.tests.assert_internal_invariants for debugging?

 
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   Pass indexes directly to the DataArray and Dataset constructors 1422543378
1293774799 https://github.com/pydata/xarray/pull/7214#issuecomment-1293774799 https://api.github.com/repos/pydata/xarray/issues/7214 IC_kwDOAMm_X85NHW_P dcherian 2448579 2022-10-27T16:21:53Z 2022-10-27T16:21:53Z MEMBER

How about Indexes.from_pandas_multi_index() classmethod?

I like the last spelling: ds.assign_indexes(indexes) though that raises a few questioins: 1. does indexes get merged with existing ._indexes? 2. If not, how does a user merge manually? Can we extract enough information from Index to have xr.merge(Indexes) -> Indexes work?

 
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   Pass indexes directly to the DataArray and Dataset constructors 1422543378

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