issue_comments: 1000287742
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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/6102#issuecomment-1000287742 | https://api.github.com/repos/pydata/xarray/issues/6102 | 1000287742 | IC_kwDOAMm_X847ny3- | 1562854 | 2021-12-23T13:00:28Z | 2021-12-23T13:00:28Z | CONTRIBUTOR | Hi @Illviljan that is correct. However after https://github.com/pydata/xarray/pull/5794 xarray is more aggressively making the pandas choice for the user. I'll play with it a bit to see if just removing your explicit registration fixes the problem. However changing the datetime converter would be a breaking change (to your plotting) that I'm not sure you want. This is a tricky problem that I'm not sure matplotlib has handled properly (full disclosure, I'm on the mpl dev team and usually handle datetime issues, though I didn't design our units registry). Having a registry that users can change is very flexible. However when downstream libraries like xarray or pandas affect user plotting just by importing the package, it leads to considerable confusion as users don't necessarily know this has happened or how to get back to the Matplotlib default. Particularly if they are not using the package's plotting utilities, but just the other features and/or data types (for instance I love xarray and use it all the time in my data analysis, but I rarely use the plotting convenience functions) |
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