issue_comments

Table actions

4 rows where author_association = "NONE" and user = 17951292 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

  • dgoldwx2112 · 4 ✖

author_association 1

  • NONE · 4 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
235742069 https://github.com/pydata/xarray/issues/919#issuecomment-235742069 https://api.github.com/repos/pydata/xarray/issues/919 MDEyOklzc3VlQ29tbWVudDIzNTc0MjA2OQ== dgoldwx2112 17951292 2016-07-27T22:32:36Z 2016-07-27T22:32:36Z NONE

Yes indeed. I'm embarrassed I even posted this! It looks like the nbnds and time_bnds variables were added to the yearly files at some point. Accordingly, a simple conditional checking for their existence and subsequently deleting them prior to concatenation did the trick. Too bad there is absolutely no consistency in these files at all.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   ValueError: encountered unexpected variable nbnds 167684282
233504857 https://github.com/pydata/xarray/issues/900#issuecomment-233504857 https://api.github.com/repos/pydata/xarray/issues/900 MDEyOklzc3VlQ29tbWVudDIzMzUwNDg1Nw== dgoldwx2112 17951292 2016-07-19T01:17:43Z 2016-07-19T01:17:43Z NONE

Thanks Stephan - that was very helpful! I was able to carry out the necessary computations with no problems after seeing your reply.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   How to apply function to two (or more) variables simultaneously 166195300
230284327 https://github.com/pydata/xarray/issues/894#issuecomment-230284327 https://api.github.com/repos/pydata/xarray/issues/894 MDEyOklzc3VlQ29tbWVudDIzMDI4NDMyNw== dgoldwx2112 17951292 2016-07-04T12:56:10Z 2016-07-04T12:56:10Z NONE

That did the trick!

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Dataset variable reference fails after renaming 163414759
229762102 https://github.com/pydata/xarray/issues/891#issuecomment-229762102 https://api.github.com/repos/pydata/xarray/issues/891 MDEyOklzc3VlQ29tbWVudDIyOTc2MjEwMg== dgoldwx2112 17951292 2016-06-30T19:22:43Z 2016-06-30T19:22:43Z NONE

Thanks, Stephan! Enjoy your vacation! For now I am processing multiple files over an opendap connection using netCDF4.MFDataset and then building a DataArray or Dataset from the variables stored within the resulting MFDataset object. This appears much faster than the process recommend here when a lot of big files are involved: http://xarray.pydata.org/en/stable/io.html (i.e., using read_netcdfs). Once a bug fix is implemented, I'll try using the dask-optimized open_mfdataset().

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   BUG: Test for dask version erroneously fails when calling xr.mfdataset() 162726984

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]);