issue_comments

Table actions

1 row where author_association = "NONE", issue = 312203596 and user = 7105759 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

  • jwindhager · 1 ✖

issue 1

  • Anyone working on a to_tiff? Alternatively, how do you write an xarray to a geotiff? · 1 ✖

author_association 1

  • NONE · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
565012344 https://github.com/pydata/xarray/issues/2042#issuecomment-565012344 https://api.github.com/repos/pydata/xarray/issues/2042 MDEyOklzc3VlQ29tbWVudDU2NTAxMjM0NA== jwindhager 7105759 2019-12-12T13:44:19Z 2019-12-12T13:44:19Z NONE

Hi! I just wrote this tiny tifffile wrapper for my own purposes, with support for xarray: https://pypi.org/project/xtiff. Not properly tested yet, but happy to take issues/pull requests (e.g. for additional write modes). Also, feel free to integrate it into xarray. The current version is xarray-agnostic, that's why I wrote it as an independent package.

 
{
    "total_count": 2,
    "+1": 2,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Anyone working on a to_tiff? Alternatively, how do you write an xarray to a geotiff?  312203596

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]);