issue_comments: 185817180
This data as json
| 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/768#issuecomment-185817180 | https://api.github.com/repos/pydata/xarray/issues/768 | 185817180 | MDEyOklzc3VlQ29tbWVudDE4NTgxNzE4MA== | 5497186 | 2016-02-18T17:05:45Z | 2016-02-18T17:34:53Z | NONE | I hadn't, for a number of reasons. First, I've used csv, hdf, sql, json, yaml and other formats but never came across netcdf until using this library as someone who isn't working in the physical sciences. Second, the documentation on netcdf is fairly dense. Third, didn't want to deal with installing the library. I just did use it and seems like it is great for Datasets. As far as I can tell there is no way to save DataArrays directly, though? Finally, would note that pandas has io methods for csv, excel, hdf, sql, json, msgpack, html, gbq, stata, "clipboard", and pickle. I think it's a strength to offer more choices. |
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