issue_comments: 517995453
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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/pull/3153#issuecomment-517995453 | https://api.github.com/repos/pydata/xarray/issues/3153 | 517995453 | MDEyOklzc3VlQ29tbWVudDUxNzk5NTQ1Mw== | 32473508 | 2019-08-04T11:29:44Z | 2019-08-04T11:30:48Z | CONTRIBUTOR | @shoyer A fix in pandas that I can imagine is to modify the pd.Index to retain the dtype similar to the PandasIndexAdapter in xarray/core/indexing. However, it seems to me that their design it to coerce any float to float64, so I did not feel they would consider this to be a bug. I would try to dig into such solution more if you recommend so. I added a test case in which the coords are float16 (in addiction to the scalar case)to show that casting to the coords type is required. The lowest level in which I can access the coords type is in the indexing/remap_label_indexers where I could get the coords from the data_obj. In the latest code, casting is done just before calling convert_label_indexer Sorry if I am missing the point, and thank you in advance for any further feedback. |
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