issues: 527323165

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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
527323165 MDU6SXNzdWU1MjczMjMxNjU= 3564 DOC: from examples to tutorials 1197350 open 0     14 2019-11-22T17:30:14Z 2023-02-21T20:01:05Z   MEMBER      

It's awesome to see the work we did at Scipy2019 finally hit the live docs! Thanks @keewis and @dcherian for pushing it through.

Now that we have these more detailed, realistic examples, let's think about how we can take our documentation to the next level. I think we need TUTORIALS. The examples are a good start. I think we can build on these to create tutorials which walk through most of xarray's core features with a domain-specific datasets. We could have different tutorials for different fields. For example.

  • Xarray tutorial for meteorology / atmospheric science
  • Xarray tutorial for oceanography
  • Xarray tutorial for physics (whatever @fujiisoup and @TomNicholas do! 😉 )
  • Xarray tutorial for finance (whatever @max-sixty and @crusaderky do! :wink:)
  • Xarray tutorial for neuroscience (see nice example from @choldgraf: https://predictablynoisy.com/xarray-explore-ieeg)

Each tutorial would cover the same core elements (loading data, indexing, aligning, grouping, computations, plotting, etc.), but using a familiar, real dataset, rather than the generic, made-up ones in our current docs.

Yes, this would be a lot of work, but I think it would have a huge impact. Just raising here for discussion.

xref #2980 #2378 #3131

 
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