DOC: from examples to tutorials

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! 😉)
• 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

No specific file, test, or entry point is named. Review the current examples and documentation, then scope domain-specific tutorials around loading data, indexing, aligning, grouping, computations, and plotting; done would mean these tutorials use familiar real datasets and cover the shared core elements.