issue_comments
1 row where issue = 170259709 and user = 5635139 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
issue 1
- Skip identical indexes with non-unique values in align? · 1 ✖
| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 238724079 | https://github.com/pydata/xarray/issues/956#issuecomment-238724079 | https://api.github.com/repos/pydata/xarray/issues/956 | MDEyOklzc3VlQ29tbWVudDIzODcyNDA3OQ== | max-sixty 5635139 | 2016-08-09T23:32:01Z | 2016-08-09T23:32:01Z | MEMBER | Another option is to fully disallow non-unique indexes. Not sure how big a use case this is, so this might be a non-starter. But two wondrous features of xarray: - Smaller & more defined surface than pandas, so not forced to have all these work arounds - Coords that aren't dimensions, so labels are possible in place of indexes |
{
"total_count": 0,
"+1": 0,
"-1": 0,
"laugh": 0,
"hooray": 0,
"confused": 0,
"heart": 0,
"rocket": 0,
"eyes": 0
} |
Skip identical indexes with non-unique values in align? 170259709 |
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