issue_comments

Table actions

2 rows where issue = 588126763 and user = 5635139 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date)

user 1

  • max-sixty · 2 ✖

issue 1

  • consecutive time selection · 2 ✖

author_association 1

id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
604779924 https://github.com/pydata/xarray/issues/3896#issuecomment-604779924 https://api.github.com/repos/pydata/xarray/issues/3896 MDEyOklzc3VlQ29tbWVudDYwNDc3OTkyNA== max-sixty 5635139 2020-03-27T02:18:48Z 2020-03-27T02:18:48Z MEMBER

OK, that's a bit harder but not impossible. You could take that, run array.astype(float).where(array).bfill(dim, limit=5), or similar? Others will probably have cleaner suggestions...

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   consecutive time selection 588126763
604499916 https://github.com/pydata/xarray/issues/3896#issuecomment-604499916 https://api.github.com/repos/pydata/xarray/issues/3896 MDEyOklzc3VlQ29tbWVudDYwNDQ5OTkxNg== max-sixty 5635139 2020-03-26T15:35:19Z 2020-03-26T15:35:19Z MEMBER

IIUC, you could have, in order: - rolling 3 month SST - bool on whether that's above 0.5 - rolling 5 month count of that - bool on whether that's equal to 5

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   consecutive time selection 588126763

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]);