issue_comments

Table actions

3 rows where author_association = "MEMBER" and issue = 605608998 sorted by updated_at descending

✖
✖
✖

✎ View and edit SQL

This data as json, CSV (advanced)

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

user 2

issue 1

  • MODIS L2 Data Missing Data Variables and Geolocation Data · 3 ✖

author_association 1

  • MEMBER · 3 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1373993285 https://github.com/pydata/xarray/issues/3996#issuecomment-1373993285 https://api.github.com/repos/pydata/xarray/issues/3996 IC_kwDOAMm_X85R5XlF rabernat 1197350 2023-01-06T18:36:56Z 2023-01-06T18:47:48Z MEMBER

We found a nice solution to this using @TomNicholas's Datatree

```python import xarray as xr import datatree

dt = datatree.open_datatree("AQUA_MODIS.20220809T182500.L2.OC.nc")

def fix_dimension_names(ds): if 'pixel_control_points' in ds.dims: ds = ds.swap_dims({'pixel_control_points': 'pixels_per_line'}) return ds

dt_fixed = dt.map_over_subtree(fix_dimension_names)

all_dsets = [subtree.ds for node, subtree in dt_fixed.items()] ds = xr.merge(all_dsets, combine_attrs="drop_conflicts") ds = ds.set_coords(['latitude', 'longitude'])

ds.chlor_a.plot(x="longitude", y="latitude", robust=True) ```

 
{
    "total_count": 1,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 1,
    "eyes": 0
}
   MODIS L2 Data Missing Data Variables and Geolocation Data 605608998
618492914 https://github.com/pydata/xarray/issues/3996#issuecomment-618492914 https://api.github.com/repos/pydata/xarray/issues/3996 MDEyOklzc3VlQ29tbWVudDYxODQ5MjkxNA== dcherian 2448579 2020-04-23T16:14:41Z 2020-04-23T16:14:41Z MEMBER

You'll have to create one dataset per group and then merge. an xarray Dataset represents one group of a netcdf file. This model unfortunately breaks down when coordinate data are only present in one group. as in your dataset

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   MODIS L2 Data Missing Data Variables and Geolocation Data 605608998
618452406 https://github.com/pydata/xarray/issues/3996#issuecomment-618452406 https://api.github.com/repos/pydata/xarray/issues/3996 MDEyOklzc3VlQ29tbWVudDYxODQ1MjQwNg== dcherian 2448579 2020-04-23T15:09:45Z 2020-04-23T15:09:45Z MEMBER

You'll need to specify group when opening the file using open_dataset: https://xarray.pydata.org/en/stable/io.html#groups

I think somewhere there is a comment saying xarray could support searching for coordinate data in groups other than the one requested. So you could look into implementing that if interested.

Either way this would make a nice example notebook for the documentation.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   MODIS L2 Data Missing Data Variables and Geolocation Data 605608998

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]);