issue_comments

Table actions

1 row where issue = 467767771 and user = 8419157 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

  • DancingQuanta · 1 ✖

issue 1

  • adding stack_all · 1 ✖

author_association 1

id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
526635815 https://github.com/pydata/xarray/pull/3115#issuecomment-526635815 https://api.github.com/repos/pydata/xarray/issues/3115 MDEyOklzc3VlQ29tbWVudDUyNjYzNTgxNQ== DancingQuanta 8419157 2019-08-30T15:02:45Z 2019-08-30T15:02:45Z NONE

Would it be possible to add exclude_dims? I have a use case where I wanted to apply a function (for example fitting) along a dimension. I programmatically create a list of dimensions to stack to create 2D dataset. Then I loop over the stacked dimension and apply the function to last dimension.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   adding stack_all 467767771

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]);