issue_comments
1 row where author_association = "MEMBER" and issue = 307444427 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
issue 1
- What is the recommended way to do proper compression/ scaling of vars? · 1 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
---|---|---|---|---|---|---|---|---|---|---|---|
375546333 | https://github.com/pydata/xarray/issues/2005#issuecomment-375546333 | https://api.github.com/repos/pydata/xarray/issues/2005 | MDEyOklzc3VlQ29tbWVudDM3NTU0NjMzMw== | shoyer 1217238 | 2018-03-23T05:05:49Z | 2018-03-23T05:05:49Z | MEMBER | You gave lots of codes examples, but it's not clear to me yet how it all fits together. Can you put it into a single code example that I can run to reproduce your problem? A minimum, complete and verifiable example would be best: https://stackoverflow.com/help/mcve |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
What is the recommended way to do proper compression/ scaling of vars? 307444427 |
Advanced export
JSON shape: default, array, newline-delimited, object
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]);
user 1