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  • fujiisoup · 2 ✖

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  • cov() and corr() · 2 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
451877705 https://github.com/pydata/xarray/pull/2652#issuecomment-451877705 https://api.github.com/repos/pydata/xarray/issues/2652 MDEyOklzc3VlQ29tbWVudDQ1MTg3NzcwNQ== fujiisoup 6815844 2019-01-07T09:43:17Z 2019-01-07T09:43:17Z MEMBER

@max-sixty I am not sure whether DataArray.dot is a right choice. But I am wondering for cov case, it sounds like to compute a covariance of the DataArray itself rather than the cross covariance with another DataArray.

 
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   cov() and corr() 396102183
451658613 https://github.com/pydata/xarray/pull/2652#issuecomment-451658613 https://api.github.com/repos/pydata/xarray/issues/2652 MDEyOklzc3VlQ29tbWVudDQ1MTY1ODYxMw== fujiisoup 6815844 2019-01-05T14:07:30Z 2019-01-05T14:07:30Z MEMBER

I am a little worrying that users could misunderstand cov is for (auto-)covariance rather than cross-covariance, which we are implementing here. Probably a function like xr.cov(x, y) is better than method?

 
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   cov() and corr() 396102183

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