issue_comments: 365796393
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| 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/1882#issuecomment-365796393 | https://api.github.com/repos/pydata/xarray/issues/1882 | 365796393 | MDEyOklzc3VlQ29tbWVudDM2NTc5NjM5Mw== | 6815844 | 2018-02-15T01:06:00Z | 2018-02-15T01:06:00Z | MEMBER | For my part, I am working in the nuclear fusion field, where we have many kinds of high-dimensional measurement data. The size of each measurement is not so huge, but we have huge kinds of data taken on different coordinates. xarray also fits such situation. (I am also happy to share my snippest but my data is not big and I am not sure this fits the tutorial concept.) xarray certainly helps me a lot, but I don't hear any usages of xarray around me. It might be a historical reason (many are still using a comersial software such as IDE). I think there is a certain market also in my field. |
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