issues: 327725925

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
327725925 MDU6SXNzdWUzMjc3MjU5MjU= 2199 HoloViews based plotting API 1550771 closed 0     10 2018-05-30T13:16:02Z 2018-07-01T12:35:56Z 2018-07-01T12:35:56Z NONE      

As part of a recent project we have been working on a plotting API for a number of projects including pandas and xarray called HoloPlot. You can see some examples using the API with xarray here. As the name suggests it is built on HoloViews and is meant as an alternative for the native plotting API that closely mirrors but does not necessarily match those APIs exactly. The main differences are:

  • Certain keywords are likely to differ, e.g. width/height vs fig_inches
  • The API returns HoloViews objects which can be composed and display themselves
  • It supports some additional features such as datashading and exploring a parameter space with widgets

The main question I'd like to put to the xarray community is how we should best expose this API. In pandas there has been some discussion to add a configurable engine for the plotting API letting you switch between different plotting implementations (see https://github.com/pandas-dev/pandas/issues/14130). The approach we started with was to clobber the DataArray.plot API entirely, which I now consider to obtrusive and likely to interfere with existing workflows. The alternative approaches we considered:

  • Name the patched method different, e.g. DataArray.hvplot, DataArray.hplot or DataArray.holoplot
  • Patch DataArray.plot but add an engine keyword to toggle between the original and HoloPlot API.
  • Add a global toggle to switch between the APIs (likely in addition to the engine keyword)

I'd love to hear what xarray maintainers and users think would be the best approach here.

 
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