issue_comments

Table actions

3 rows where issue = 771484861 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

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

issue 1

  • ⚠️ Nightly upstream-dev CI failed ⚠️ · 3 ✖

author_association 1

id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
749205535 https://github.com/pydata/xarray/issues/4717#issuecomment-749205535 https://api.github.com/repos/pydata/xarray/issues/4717 MDEyOklzc3VlQ29tbWVudDc0OTIwNTUzNQ== TomAugspurger 1312546 2020-12-21T21:29:56Z 2020-12-21T21:29:56Z MEMBER

I'm not sure offhand. Maybe best to post an issue on the pandas tracker.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   ⚠️ Nightly upstream-dev CI failed ⚠️ 771484861
749201672 https://github.com/pydata/xarray/issues/4717#issuecomment-749201672 https://api.github.com/repos/pydata/xarray/issues/4717 MDEyOklzc3VlQ29tbWVudDc0OTIwMTY3Mg== dcherian 2448579 2020-12-21T21:21:19Z 2020-12-21T21:21:19Z MEMBER

But maybe we should just ask the pandas devs whether that was intentional?

cc @TomAugspurger 

{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   ⚠️ Nightly upstream-dev CI failed ⚠️ 771484861
748677944 https://github.com/pydata/xarray/issues/4717#issuecomment-748677944 https://api.github.com/repos/pydata/xarray/issues/4717 MDEyOklzc3VlQ29tbWVudDc0ODY3Nzk0NA== keewis 14808389 2020-12-20T22:11:54Z 2020-12-20T22:42:46Z MEMBER

this fails because pandas changed the way they treat dask arrays passed to their constructor: we now get a series of object dtype filled with 0d dask arrays.

We can work around that by computing x before passing it to pandas.DataFrame in the to_dask_dataframe tests: python expected_pd = pd.DataFrame({"a": x.compute(), "b": y}, index=pd.Index(t, name="t")) or by assigning the initial numpy array to x and converting it to a dask array immediately before passing it to the xr.Dataset constructor: ```python x = np.random.randn(10)

...

ds = xr.Dataset({"a": ("t", da.from_array(x, chunks=4)), "b": ("t", y), "t": ("t", t)}) ``` (and something similar for the other two failing tests)

But maybe we should just ask the pandas devs whether that was intentional?

 
{
    "total_count": 1,
    "+1": 1,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   ⚠️ Nightly upstream-dev CI failed ⚠️ 771484861

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]);