issue_comments: 401195638
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/2256#issuecomment-401195638 | https://api.github.com/repos/pydata/xarray/issues/2256 | 401195638 | MDEyOklzc3VlQ29tbWVudDQwMTE5NTYzOA== | 4338975 | 2018-06-28T22:46:32Z | 2018-06-28T22:47:09Z | NONE | Yes I agree Zarr is best for large arrays etc. that's kid of why I ended up on the array of xray objects idea. I guess that was sort of creating an object store in zarr. What I'd like to offer is a simple set of analytical tools based on jupyter allowing for easy processing of float data, getting away from the download and process pattern. I'm still trying to find the best way to do this as Argo data does not neatly fall into any one system because of it's lack of homogeneity |
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