issue_comments: 434480457

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https://github.com/pydata/xarray/issues/2525#issuecomment-434480457 https://api.github.com/repos/pydata/xarray/issues/2525 434480457 MDEyOklzc3VlQ29tbWVudDQzNDQ4MDQ1Nw== 1197350 2018-10-30T21:41:17Z 2018-10-30T21:41:25Z MEMBER

I would lean towards a coordinate based representation since it's a little more usable/certain to be correct.

I feel that this could become too complex in the case of irregularly spaced coordinates. I slightly favor the index-based approach (as in my function above), which one calls like python aggregate_da(da, {'lat': 2, 'lon': 2})

If we do that, we can just use scikit-image's block_reduce function, which is vectorized and works great with apply_ufunc.

 
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