issue_comments
1 row where issue = 564555854 and user = 2448579 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
issue 1
- Pointwise indexing · 1 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
---|---|---|---|---|---|---|---|---|---|---|---|
585820745 | https://github.com/pydata/xarray/issues/3768#issuecomment-585820745 | https://api.github.com/repos/pydata/xarray/issues/3768 | MDEyOklzc3VlQ29tbWVudDU4NTgyMDc0NQ== | dcherian 2448579 | 2020-02-13T15:38:56Z | 2020-02-13T15:38:56Z | MEMBER | The documentation for what you want is here: https://xarray.pydata.org/en/stable/indexing.html#more-advanced-indexing. Basically you need to provide DataArrays with a new dimension instead of lists. PRs to improve the documentation are very welcome (ref https://github.com/pydata/xarray/issues/1552). We actually have a nice schematic here: https://xarray.pydata.org/en/stable/interpolation.html#advanced-interpolation |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Pointwise indexing 564555854 |
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