issue_comments: 129189753
This data as json
| 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/521#issuecomment-129189753 | https://api.github.com/repos/pydata/xarray/issues/521 | 129189753 | MDEyOklzc3VlQ29tbWVudDEyOTE4OTc1Mw== | 1197350 | 2015-08-09T14:00:37Z | 2015-08-09T14:00:37Z | MEMBER | @jhamman Thanks for the clear explanation! One of the main uses for non-standard calendars would be climate model "control runs", which don't occur any any specific point in historical time but still have seasonal cycles, well defined months, etc. It would be nice to have "group by" functionality for these datasets. But I do see how this is impossible with the current numpy datetime64 datatype. Perhaps the long term fix is to implement non-standard calendars within numpy itself. |
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