issue_comments

Table actions

1 row where author_association = "CONTRIBUTOR" and issue = 1471685307 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date), updated_at (date)

user 1

issue 1

  • Disable bottleneck by default? · 1 ✖

author_association 1

  • CONTRIBUTOR · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1351398850 https://github.com/pydata/xarray/issues/7344#issuecomment-1351398850 https://api.github.com/repos/pydata/xarray/issues/7344 IC_kwDOAMm_X85QjLXC markelg 6883049 2022-12-14T13:54:06Z 2022-12-14T13:54:06Z CONTRIBUTOR

I fully agree that correctness is the priority. Note however that some functions now require bottleneck, like ffill and bfill (I am not sure if there are more cases). They may need to be modified so they can run without bottleneck.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Disable bottleneck by default? 1471685307

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

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]);