issue_comments

Table actions

1 row where issue = 205473898 and user = 5179430 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

  • agoodm · 1 ✖

issue 1

  • CFTimeIndex · 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
380580598 https://github.com/pydata/xarray/pull/1252#issuecomment-380580598 https://api.github.com/repos/pydata/xarray/issues/1252 MDEyOklzc3VlQ29tbWVudDM4MDU4MDU5OA== agoodm 5179430 2018-04-11T20:11:44Z 2018-04-11T20:14:43Z CONTRIBUTOR

Hi all, any updates on the current status for this? This will be a big help for me as well in particular for processing daily CMIP5 netcdf files. I have been following this thread as well as the original issue and really appreciate this work. One other question: This PR doesn't allow for resampling on non-standard calendars as is, but I remember @shoyer mentioning that a workaround using pandas Grouper objects will exist. Would someone be able to explain to me how this would work? Thanks!

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   CFTimeIndex 205473898

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]);