issue_comments

Table actions

1 row where author_association = "MEMBER" and issue = 546956885 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date), updated_at (date)

user 1

issue 1

  • Feature request: pull StackExchange answer into "How Do I?" · 1 ✖

author_association 1

  • MEMBER · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
572191138 https://github.com/pydata/xarray/issues/3672#issuecomment-572191138 https://api.github.com/repos/pydata/xarray/issues/3672 MDEyOklzc3VlQ29tbWVudDU3MjE5MTEzOA== dcherian 2448579 2020-01-08T18:14:28Z 2020-01-08T18:14:28Z MEMBER

That looks great. But maybe this looks complicated enough to be in a "Data reorganization" example notebook? We can then link to that notebook in the "how do I" table.

What do you think? Can you send in a PR?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Feature request: pull StackExchange answer into "How Do I?" 546956885

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

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]);