issue_comments

Table actions

6 rows where issue = 158078410 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date), updated_at (date)

author_association 2

issue 1

  • How to reduce the output size with to_netcdf? · 6 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1225823013 https://github.com/pydata/xarray/issues/865#issuecomment-1225823013 https://api.github.com/repos/pydata/xarray/issues/865 IC_kwDOAMm_X85JEJMl marcosrdac 7348840 2022-08-24T14:42:47Z 2022-08-24T14:42:47Z NONE

You can also use zlib and complevel

Just making it clear: those would configure lossless compression of netcdf4 lib, not lossy compression.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   How to reduce the output size with to_netcdf? 158078410
1220723134 https://github.com/pydata/xarray/issues/865#issuecomment-1220723134 https://api.github.com/repos/pydata/xarray/issues/865 IC_kwDOAMm_X85IwsG- dcherian 2448579 2022-08-19T14:07:00Z 2022-08-19T14:07:16Z MEMBER

You can also use zlib and complevel

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   How to reduce the output size with to_netcdf? 158078410
1220093929 https://github.com/pydata/xarray/issues/865#issuecomment-1220093929 https://api.github.com/repos/pydata/xarray/issues/865 IC_kwDOAMm_X85IuSfp marcosrdac 7348840 2022-08-19T00:04:21Z 2022-08-19T00:04:21Z NONE

Thanks, I thought there were some methods to choose from or something like that. For future readers, scale_factor seems to be used to control compression loss.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   How to reduce the output size with to_netcdf? 158078410
1219728490 https://github.com/pydata/xarray/issues/865#issuecomment-1219728490 https://api.github.com/repos/pydata/xarray/issues/865 IC_kwDOAMm_X85Is5Rq dcherian 2448579 2022-08-18T17:04:09Z 2022-08-18T17:04:09Z MEMBER

Please read the documentation

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   How to reduce the output size with to_netcdf? 158078410
1219669758 https://github.com/pydata/xarray/issues/865#issuecomment-1219669758 https://api.github.com/repos/pydata/xarray/issues/865 IC_kwDOAMm_X85Isq7- marcosrdac 7348840 2022-08-18T16:01:58Z 2022-08-18T16:01:58Z NONE

How do I get lossy compression? I could not find it on the documentation :(

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   How to reduce the output size with to_netcdf? 158078410
223516527 https://github.com/pydata/xarray/issues/865#issuecomment-223516527 https://api.github.com/repos/pydata/xarray/issues/865 MDEyOklzc3VlQ29tbWVudDIyMzUxNjUyNw== fmaussion 10050469 2016-06-03T08:05:13Z 2016-06-03T08:05:13Z MEMBER

NetCDF and xarray support lossy compression (extremely efficient and fast with the cost of numerical precision loss) or gzip compression (without precision loss but with slower I/O - especially when reading chunks of data). You can have a look at the documentation about NetCDF I/O here.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   How to reduce the output size with to_netcdf? 158078410

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]);