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  • rabernat · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
393292090 https://github.com/pydata/xarray/issues/2199#issuecomment-393292090 https://api.github.com/repos/pydata/xarray/issues/2199 MDEyOklzc3VlQ29tbWVudDM5MzI5MjA5MA== rabernat 1197350 2018-05-30T19:42:43Z 2018-05-30T19:42:43Z MEMBER

Oh and another big 👍 to the datashader integration. This is crucial for my datasets.

 
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   HoloViews based plotting API 327725925
393291809 https://github.com/pydata/xarray/issues/2199#issuecomment-393291809 https://api.github.com/repos/pydata/xarray/issues/2199 MDEyOklzc3VlQ29tbWVudDM5MzI5MTgwOQ== rabernat 1197350 2018-05-30T19:41:56Z 2018-05-30T19:41:56Z MEMBER

I am a big fan of holoviews and have been using it extensively for my own work in recent months. So obviously I am a big 👍 on this integration.

I agree the accessor is the best option for now, but I have no strong opinions about the name of the accessor.

Some features I would like to see are things that go beyond the plotting capabilities associated with the matplotlib engine. For example:

  • Automatic generation of DynamicMaps. Say I have a DataArray with dimensions ('time', 'lat', 'lon'); I should be able to say da.hv.plot(kdims=['lat', 'lon'] and have time become a dynamic selector.
  • To go along with the above, lazy loading of dask-backed arrays
  • Intelligent faceting which automatically links the facet kdims
  • Plotting not just of DataArrays but Datasets. The variable itself could become a dynamic selector in a dropdown menu. Basically, I just want to say ds.hv.plot() and have holoviews provide all the options I need to explore the dataset interactively. Kind of like how ncview works. At that point, we won't need ncview anymore.
  • Options for projections, coastlines, etc. associated with geoviews
 
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   HoloViews based plotting API 327725925

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