issue_comments

Table actions

1 row where issue = 479942077 and user = 5311739 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

  • oliverhiggs · 1 ✖

issue 1

  • How should xarray use/support sparse arrays? · 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
550966385 https://github.com/pydata/xarray/issues/3213#issuecomment-550966385 https://api.github.com/repos/pydata/xarray/issues/3213 MDEyOklzc3VlQ29tbWVudDU1MDk2NjM4NQ== oliverhiggs 5311739 2019-11-07T07:57:17Z 2019-11-07T07:57:17Z NONE

Thanks for rolling out support for sparse arrays!

I think it would be great to have a sparse argument in the concat function. This will be useful with join='outer', as the resultant DataArray/Dataset can become quite sparse.

As an example, I have a use case where I want to concatenate (across a new dimension) a number of DataArrays with date indexes covering different date ranges. When I use concat the memory used by the resultant array is much greater than that used by the original list of DataArrays due to the large number of NA values that appear in it.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   How should xarray use/support sparse arrays? 479942077

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]);