issue_comments

Table actions

1 row where issue = 332471780 and user = 6598749 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

  • angelra · 1 ✖

issue 1

  • Problem opening unstructured grid ocean forecasts with 4D vertical coordinates · 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
641410484 https://github.com/pydata/xarray/issues/2233#issuecomment-641410484 https://api.github.com/repos/pydata/xarray/issues/2233 MDEyOklzc3VlQ29tbWVudDY0MTQxMDQ4NA== angelra 6598749 2020-06-09T16:18:21Z 2020-06-09T16:18:21Z NONE

I had to go around this issue and not use xarray but pandas instead or plain netdcf4

nc = netCDF4.Dataset(input_file) h = nc.variables[vname] times = nc.variables['time'] jd = netCDF4.num2date(times[:],times.units) hs = pd.Series(h[:,station],index=jd)

I would love to know if there is a way to do it over xarray since it is so nice to use. Best regards

 
{
    "total_count": 2,
    "+1": 2,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Problem opening unstructured grid ocean forecasts with 4D vertical coordinates 332471780

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]);