issue_comments: 850556738

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https://github.com/pydata/xarray/pull/5390#issuecomment-850556738 https://api.github.com/repos/pydata/xarray/issues/5390 850556738 MDEyOklzc3VlQ29tbWVudDg1MDU1NjczOA== 56925856 2021-05-28T17:12:52Z 2021-05-28T17:14:08Z CONTRIBUTOR

@willirath this is great stuff, thanks again! So generally it looks like the graph is more efficient when doing operations of the form:

python3 (X * Y).mean('time') - (X.mean('time') * Y.mean('time'))

than doing python3 ((X - X.mean('time')) * (Y-Y.mean('time'))).mean('time')

or like what I've implemented (see screenshot)? ```python3 intermediate = (X * Y) - (X.mean('time') * Y.mean('time'))

intermediate.mean('time') ```

If so, it seems like the most efficient(?) way to do the computation in _cov_corr() is to combine it all into one line? I can't think of how to do this though...

 
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