issue_comments: 422098003
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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/1613#issuecomment-422098003 | https://api.github.com/repos/pydata/xarray/issues/1613 | 422098003 | MDEyOklzc3VlQ29tbWVudDQyMjA5ODAwMw== | 10050469 | 2018-09-17T17:17:18Z | 2018-09-17T17:17:18Z | MEMBER |
This is very frequent for climate models also (lat arrays are frequently upside down). An xarray (or upstream) solution would be very useful indeed, but possibly there are other things to consider, like being "too magical". xarray makes a very good job at handling decreasing coordinates (i.e. when plotting), but soon or late users might need to know how they data is ordered, and indexing might be the right time to warn them about it when they do something wrong: usually an empty array is unlikely to be left unnoticed, so that the current behavior might help to find bugs in user code. |
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