issue_comments

Table actions

1 row where author_association = "MEMBER", issue = 351000813 and user = 1217238 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

  • shoyer · 1 ✖

issue 1

  • Inconsistent results when calculating sums on float32 arrays w/ bottleneck installed · 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
413775977 https://github.com/pydata/xarray/issues/2370#issuecomment-413775977 https://api.github.com/repos/pydata/xarray/issues/2370 MDEyOklzc3VlQ29tbWVudDQxMzc3NTk3Nw== shoyer 1217238 2018-08-17T06:58:21Z 2018-08-17T06:58:21Z MEMBER

There has been discussion about changing this condo-forge dependencies for xarray: https://github.com/conda-forge/xarray-feedstock/issues/5. Bottleneck definitely isn’t a true required dependency.

Does it work to simply specify an explicit dtype in the sum?

I also wonder if it’s really worth the hassle of using bottleneck here, given these numerical precision issues and how it can’t be used with cask. But I do think it still probably offers a meaningful speedup in many cases....

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Inconsistent results when calculating sums on float32 arrays w/ bottleneck installed 351000813

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]);