issue_comments: 577772787
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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 |
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https://github.com/pydata/xarray/issues/3709#issuecomment-577772787 | https://api.github.com/repos/pydata/xarray/issues/3709 | 577772787 | MDEyOklzc3VlQ29tbWVudDU3Nzc3Mjc4Nw== | 1695496 | 2020-01-23T16:58:45Z | 2020-01-23T20:09:35Z | CONTRIBUTOR |
On the one hand, yes, HoloViews + Panel is quite powerful and clean for what it can already do. But just so everyone is on the same page, the workflow @philippjfr shows above is only possible for the operations that HoloViews has implemented internally. The operations available in HoloViews are only a small subset of what can be done with the native Xarray or Pandas APIs, and adding new capability like that to HoloViews is difficult because HoloViews supports many different underlying data formats (lists, dictionaries, NumPy, Pandas, Xarray, etc.). So while there are advantages to what's already available in HoloViews:
there are also major disadvantages:
Note that hvPlot injects the plotting capability from HoloViews into Xarray and Pandas, letting you use the native data APIs for plotting, but it doesn't give you the control over lazy/interactive/reactive pipelines that HoloViews' native API offers. So to me what this issue's proposal would entail is taking the idea of hvPlot further, making Xarray (and Pandas) natively act like HoloViews already does -- with lazy operations where interactive controls can be inserted at every stage, letting people stay in their preferred rich, native data API while having the power to easily make anything interactive and to easily make anything visualizable. |
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