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1 row where issue = 1249095540 and user = 5635139 sorted by updated_at descending

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  • max-sixty · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1139098672 https://github.com/pydata/xarray/pull/6638#issuecomment-1139098672 https://api.github.com/repos/pydata/xarray/issues/6638 IC_kwDOAMm_X85D5UQw max-sixty 5635139 2022-05-26T22:01:55Z 2022-05-26T22:01:55Z MEMBER

Because we want an all-NaN slice to return NaN for corr, this doesn't work — we would need to add another transformation to mask out those slices after, when then requires another pass.

If there were a numba implementation of corr or cov, that would be far more performant than these, which are doing multiple passes & copies of each array, as well as blowing out any single-dimensions with the align.

I'll close this. If anyone has alternative ideas, please feel free to raise.

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  Improve perf of xr.corr 1249095540

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CREATE TABLE [issue_comments] (
   [html_url] TEXT,
   [issue_url] TEXT,
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [created_at] TEXT,
   [updated_at] TEXT,
   [author_association] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [issue] INTEGER REFERENCES [issues]([id])
);
CREATE INDEX [idx_issue_comments_issue]
    ON [issue_comments] ([issue]);
CREATE INDEX [idx_issue_comments_user]
    ON [issue_comments] ([user]);
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