issue_comments
1 row where issue = 270440308 and user = 2656596 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
issue 1
- Serializing attrs · 1 ✖
| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 341241720 | https://github.com/pydata/xarray/issues/1681#issuecomment-341241720 | https://api.github.com/repos/pydata/xarray/issues/1681 | MDEyOklzc3VlQ29tbWVudDM0MTI0MTcyMA== | mullenkamp 2656596 | 2017-11-01T21:03:10Z | 2017-11-02T04:45:12Z | NONE | Thanks for the reply.
I'm currently using netcdf4 version 1.2.2, which seems slightly old but that's the default conda package.
Ok, so just to clarify...
The Thanks again. |
{
"total_count": 0,
"+1": 0,
"-1": 0,
"laugh": 0,
"hooray": 0,
"confused": 0,
"heart": 0,
"rocket": 0,
"eyes": 0
} |
Serializing attrs 270440308 |
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