issue_comments: 739904265
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| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| https://github.com/pydata/xarray/issues/3929#issuecomment-739904265 | https://api.github.com/repos/pydata/xarray/issues/3929 | 739904265 | MDEyOklzc3VlQ29tbWVudDczOTkwNDI2NQ== | 29051639 | 2020-12-07T13:01:57Z | 2020-12-07T13:02:20Z | CONTRIBUTOR | One of the things I was hoping to include in my approach is the preservation of the column dimension names, however if I was to use Thanks for the advice @shoyer, I reached a similar opinion and so have been working on the dim compute route. The issue is that a Dask array's shape uses np.nan for uncomputed dimensions, rather than leaving a delayed object like the Dask dataframe's shape. I looked into returning the dask dataframe rather than dask array but this didn't feel like it fit with the rest of the code and produced another issue as dask dataframes don't have a dtype attribute. I'll continue to look into alternatives. |
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