html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/2805#issuecomment-471768511,https://api.github.com/repos/pydata/xarray/issues/2805,471768511,MDEyOklzc3VlQ29tbWVudDQ3MTc2ODUxMQ==,1217238,2019-03-11T22:40:28Z,2019-03-11T22:40:28Z,MEMBER,"You could convert your data into pandas and use `.itertuples()`, e.g.,
```python
import xarray
import itertools

ds = xarray.tutorial.open_dataset('air_temperature')
records = ds.to_dataframe().reset_index().itertuples(index=False, name='Record')
print(list(itertools.islice(records, 5)))
```
Outputs:
```
[Record(lat=75.0, lon=200.0, time=Timestamp('2013-01-01 00:00:00'), air=241.1999969482422),
 Record(lat=75.0, lon=200.0, time=Timestamp('2013-01-01 06:00:00'), air=242.09999084472656),
 Record(lat=75.0, lon=200.0, time=Timestamp('2013-01-01 12:00:00'), air=242.29998779296875),
 Record(lat=75.0, lon=200.0, time=Timestamp('2013-01-01 18:00:00'), air=241.88999938964844),
 Record(lat=75.0, lon=200.0, time=Timestamp('2013-01-02 00:00:00'), air=243.1999969482422)]
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,419543087