issue_comments

Table actions

5 rows where author_association = "MEMBER" and issue = 882876804 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 3

issue 1

  • Dask-friendly nan check in xr.corr() and xr.cov() · 5 ✖

author_association 1

  • MEMBER · 5 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
849811814 https://github.com/pydata/xarray/pull/5284#issuecomment-849811814 https://api.github.com/repos/pydata/xarray/issues/5284 MDEyOklzc3VlQ29tbWVudDg0OTgxMTgxNA== max-sixty 5635139 2021-05-27T17:31:02Z 2021-05-27T17:31:02Z MEMBER

Thank you very much @AndrewWilliams3142 !

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Dask-friendly nan check in xr.corr() and xr.cov() 882876804
849169576 https://github.com/pydata/xarray/pull/5284#issuecomment-849169576 https://api.github.com/repos/pydata/xarray/issues/5284 MDEyOklzc3VlQ29tbWVudDg0OTE2OTU3Ng== max-sixty 5635139 2021-05-26T22:46:43Z 2021-05-26T22:46:43Z MEMBER

Please feel free to add a whatsnew @AndrewWilliams3142 

{
    "total_count": 1,
    "+1": 1,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Dask-friendly nan check in xr.corr() and xr.cov() 882876804
837097308 https://github.com/pydata/xarray/pull/5284#issuecomment-837097308 https://api.github.com/repos/pydata/xarray/issues/5284 MDEyOklzc3VlQ29tbWVudDgzNzA5NzMwOA== dcherian 2448579 2021-05-10T18:25:29Z 2021-05-10T18:25:29Z MEMBER

Well that was confusing! if missing_vals.any(): will not be triggered if all the values in a block are valid. With .chunk({"time": 1}), some of the blocks are all valid.

I discovered this with print debugging and the single-threaded scheduler which loops over blocks in a for-loop ```

Define function to use in map_blocks

def _get_valid_values(da, other): da1, da2 = xr.align(da, other, join="inner", copy=False)

# 2. Ignore the nans
missing_vals = np.logical_or(da1.isnull(), da2.isnull())
print(missing_vals)

if missing_vals.any():
    da = da.where(missing_vals)
return da

da_a.map_blocks(_get_valid_values, args=[da_b]).compute(scheduler="sync") ```

For better performance, we should try a dask.array.map_blocks approach with duck_array_ops.isnull 

{
    "total_count": 1,
    "+1": 1,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Dask-friendly nan check in xr.corr() and xr.cov() 882876804
837045902 https://github.com/pydata/xarray/pull/5284#issuecomment-837045902 https://api.github.com/repos/pydata/xarray/issues/5284 MDEyOklzc3VlQ29tbWVudDgzNzA0NTkwMg== keewis 14808389 2021-05-10T17:53:05Z 2021-05-10T17:53:05Z MEMBER

4559 and #4668 fixed a similar issue using map_blocks, maybe you can use that as a reference?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Dask-friendly nan check in xr.corr() and xr.cov() 882876804
835907226 https://github.com/pydata/xarray/pull/5284#issuecomment-835907226 https://api.github.com/repos/pydata/xarray/issues/5284 MDEyOklzc3VlQ29tbWVudDgzNTkwNzIyNg== max-sixty 5635139 2021-05-09T22:15:25Z 2021-05-09T22:15:25Z MEMBER

Hi @AndrewWilliams3142 , thanks for another PR!

This looks good. Could we add a test like https://github.com/pydata/xarray/pull/4559/files#diff-74d2dc289aa601b2de094fb3a3b687fd65963401b51b95cc5e0afcd06cc4cb82R45? And maybe reference this or #4559 as an explanation of what's going on.

 
{
    "total_count": 1,
    "+1": 1,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Dask-friendly nan check in xr.corr() and xr.cov() 882876804

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]);