issue_comments

Table actions

1 row where author_association = "CONTRIBUTOR", issue = 238990919 and user = 14314623 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

  • jbusecke · 1 ✖

issue 1

  • CF conventions for time doesn't support years · 1 ✖

author_association 1

  • CONTRIBUTOR · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
465760182 https://github.com/pydata/xarray/issues/1467#issuecomment-465760182 https://api.github.com/repos/pydata/xarray/issues/1467 MDEyOklzc3VlQ29tbWVudDQ2NTc2MDE4Mg== jbusecke 14314623 2019-02-20T21:25:01Z 2019-02-20T21:25:01Z CONTRIBUTOR

I have run into this problem multiple times. The latest example I found were some [CORE ocean model runs] (https://rda.ucar.edu/datasets/ds262.0/index.html#!description). The time dimension of some (they mix units) of these files is given as netcdf MRI-A_sigma0_monthly { dimensions: level = 51 ; latitude = 368 ; longitude = 364 ; time = UNLIMITED ; // (720 currently) time_bnds = 2 ; variables: double latitude(latitude) ; latitude:units = "degrees_north " ; latitude:axis = "Y" ; double longitude(longitude) ; longitude:units = "degrees_east " ; longitude:axis = "X" ; double level(level) ; level:units = "m " ; level:axis = "Z" ; double time(time) ; time:units = "years since 1948-1-1 00:00:00 " ; time:axis = "T" ; time:bounds = "time_bnds" ; time:calendar = "noleap" ; double time_bnds(time, time_bnds) ; float sigma0(time, level, latitude, longitude) ; sigma0:units = "kg/m^3 " ; sigma0:long_name = "Monthly-mean potential density (sigma-0) " ; sigma0:missing_value = -9.99e+33f ; }

I understand that 'fully' supporting to decode this unit is hard and should probably addressed upstream.

But I think it might be useful to have a utility function that converts a dataset with these units into someting quickly useable with xarray? E.g. one could load the dataset with ds = xr.open_dataset(..., decode_times=False) and then maybe call xr.decode_funky_units(ds, units='calendaryears', ...), which could default to the first day of a year (or the first day of a month for units of months since.

This way the user is aware that something is not decoded exactly, but can work with the data. Is this something that people could see useful here? Id be happy to give an implementation a shot if there is interest. 

{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   CF conventions for time doesn't support years 238990919

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]);