issue_comments

Table actions

1 row where author_association = "NONE" and user = 5564291 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

  • betaplane · 1 ✖

author_association 1

  • NONE · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
322926397 https://github.com/pydata/xarray/issues/1509#issuecomment-322926397 https://api.github.com/repos/pydata/xarray/issues/1509 MDEyOklzc3VlQ29tbWVudDMyMjkyNjM5Nw== betaplane 5564291 2017-08-16T23:23:38Z 2017-08-16T23:23:38Z NONE

Ok, thanks a lot. Just as a comment though, pandas does it differently, and the xarray documentation states that "resample uses essentially the same api as resample in pandas." ``` In [1]: import numpy as np

In [2]: import pandas as pd

In [3]: x = pd.DataFrame([1, np.nan], pd.date_range('2017-08-01', '2017-08-02'))

In [4]: x.resample('D').mean() Out[4]: 0 2017-08-01 1.0 2017-08-02 NaN

In [5]: x.resample('D').sum() Out[5]: 0 2017-08-01 1.0 2017-08-02 NaN ```

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Unexpected behavior with DataArray.resample(how='sum') in presence of NaNs 250751931

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]);