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1 row where author_association = "MEMBER", issue = 427644858 and user = 1217238 sorted by updated_at descending

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user 1

  • shoyer · 1 ✖

issue 1

  • WHERE function, problems with memory operations? · 1 ✖

author_association 1

  • MEMBER · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
478750808 https://github.com/pydata/xarray/issues/2861#issuecomment-478750808 https://api.github.com/repos/pydata/xarray/issues/2861 MDEyOklzc3VlQ29tbWVudDQ3ODc1MDgwOA== shoyer 1217238 2019-04-01T21:14:56Z 2019-04-01T21:14:56Z MEMBER

The usual recommendation is to align all of your separate datasets onto the same grid before combining them. reindex_like() and interp_like() make this pretty easy, e.g., proof.interp_like(ref).

{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
  WHERE function, problems with memory operations? 427644858

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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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