issue_comments

Table actions

1 row where issue = 462424005 and user = 4903456 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

  • mrezak · 1 ✖

issue 1

  • xarray rolling does not match pandas when using min_periods and reduce · 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
508295570 https://github.com/pydata/xarray/issues/3066#issuecomment-508295570 https://api.github.com/repos/pydata/xarray/issues/3066 MDEyOklzc3VlQ29tbWVudDUwODI5NTU3MA== mrezak 4903456 2019-07-04T00:23:45Z 2019-07-04T00:23:45Z NONE

@shoyer thanks for looking into this.

I also figured it later that I can just use np.nanmean (or nanmedian) but that function turns out to be much slower than np.mean (or np.median) version. As nans are only happening as the beginning and end of the sequence, is there any efficient way of using nanmean only for those segments and mean for the rest of the processing? My own thought is to have a check for nan in the custom function and apply mean or nanmean depending on the results of that check, but not sure if this can be done more efficiently.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   xarray rolling does not match pandas when using min_periods and reduce 462424005

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]);