issue_comments

Table actions

2 rows where author_association = "MEMBER", issue = 1611288905 and user = 14808389 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date)

user 1

  • keewis · 2 ✖

issue 1

  • xr.where increase the bytes of the dataset · 2 ✖

author_association 1

  • MEMBER · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1456139058 https://github.com/pydata/xarray/issues/7587#issuecomment-1456139058 https://api.github.com/repos/pydata/xarray/issues/7587 IC_kwDOAMm_X85Wyusy keewis 14808389 2023-03-06T13:29:14Z 2023-03-06T13:29:14Z MEMBER

thanks, that helps. However, it does not confirm my suspicion since all data variables are already in float64, and thus they shouldn't change dtypes. Could you also post the repr (either the text or the html repr should be sufficient) of a, and maybe also the file type of the file you're loading the dataset from (ifileFamBulk)?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   xr.where increase the bytes of the dataset  1611288905
1456063239 https://github.com/pydata/xarray/issues/7587#issuecomment-1456063239 https://api.github.com/repos/pydata/xarray/issues/7587 IC_kwDOAMm_X85WycMH keewis 14808389 2023-03-06T12:41:24Z 2023-03-06T12:41:49Z MEMBER

I can't really tell from the information you posted so far. Could you post the repr of da_fam_bulk (print(da_fam_bulk) or display(da_fam_bulk) using ipython / jupyter, plus maybe a screenshot of the HTML repr if you're in a notebook)?

I do suspect, however, that da_fam_bulk has a dtype that is not float64, but where will use float64(nan) as a fill value, casting the entire array to a dtype that has a much higher memory usage.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   xr.where increase the bytes of the dataset  1611288905

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]);