issue_comments

Table actions

1 row where author_association = "MEMBER", issue = 593029940 and user = 14808389 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

  • keewis · 1 ✖

issue 1

  • Feature request xarray.Dataset.from_dask_dataframe · 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
739395190 https://github.com/pydata/xarray/issues/3929#issuecomment-739395190 https://api.github.com/repos/pydata/xarray/issues/3929 MDEyOklzc3VlQ29tbWVudDczOTM5NTE5MA== keewis 14808389 2020-12-05T20:13:58Z 2020-12-05T20:44:42Z MEMBER

Thanks for investigating and working on this, @AyrtonB.

I indeed think this is the correct place to discuss this: your use case can probably be implemented by converting to a Dataset and then calling Dataset.to_array. Actually, we currently implement most methods on DataArray objects by converting to a temporary single-variable Dataset, calling the equivalent Dataset method and then converting the result back to a DataArray.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Feature request xarray.Dataset.from_dask_dataframe 593029940

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]);