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  • hrishikeshac · 2 ✖

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  • cov() and corr() · 2 ✖

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  • NONE · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
452782113 https://github.com/pydata/xarray/pull/2652#issuecomment-452782113 https://api.github.com/repos/pydata/xarray/issues/2652 MDEyOklzc3VlQ29tbWVudDQ1Mjc4MjExMw== hrishikeshac 6334793 2019-01-09T17:32:12Z 2019-01-09T17:32:12Z NONE

I also think making this a function is probably a good idea, even though it's different from pandas.

One question: how should these functions align their arguments? Recall that xarray does an inner join for arithmetic (though there's an option to control this), and an outer join in most other cases. It's not entirely obvious to me what the right choice is here (or if it really even matters).

I always assumed an inner join is the way to go. I had initially just implemented align, but later changed to broadcast since the align doesn't add dimension/ labels (if missing in one of the inputs) to the output, but broadcast does. Without this, the where(valid_values) doesn't work if one input is 1-D and the other is N-D. 

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   cov() and corr() 396102183
451602256 https://github.com/pydata/xarray/pull/2652#issuecomment-451602256 https://api.github.com/repos/pydata/xarray/issues/2652 MDEyOklzc3VlQ29tbWVudDQ1MTYwMjI1Ng== hrishikeshac 6334793 2019-01-04T23:44:10Z 2019-01-04T23:44:10Z NONE

Made the code PEP8 compatible. Apologies for not doing so earlier. 

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   cov() and corr() 396102183

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