issue_comments
2 rows where "updated_at" is on date 2017-11-07 sorted by updated_at descending
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user 1
- simonw 2
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | issue | performed_via_github_app |
---|---|---|---|---|---|---|---|---|---|---|---|
342521344 | https://github.com/simonw/datasette/issues/47#issuecomment-342521344 | https://api.github.com/repos/simonw/datasette/issues/47 | MDEyOklzc3VlQ29tbWVudDM0MjUyMTM0NA== | simonw 9599 | 2017-11-07T15:37:45Z | 2017-11-07T15:37:45Z | OWNER | GDS Registries could be fun too: https://registers.cloudapps.digital/ |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Create neat example database 271831408 | |
342484889 | https://github.com/simonw/datasette/issues/44#issuecomment-342484889 | https://api.github.com/repos/simonw/datasette/issues/44 | MDEyOklzc3VlQ29tbWVudDM0MjQ4NDg4OQ== | simonw 9599 | 2017-11-07T13:39:49Z | 2017-11-07T13:39:49Z | OWNER | I’m going to call this feature “count values” |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
?_group_count=country - return counts by specific column(s) 269731374 |
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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, [issue] INTEGER REFERENCES [issues]([id]) , [performed_via_github_app] TEXT); CREATE INDEX [idx_issue_comments_issue] ON [issue_comments] ([issue]); CREATE INDEX [idx_issue_comments_user] ON [issue_comments] ([user]);
issue 2