issue_comments: 605697466
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/1194#issuecomment-605697466 | https://api.github.com/repos/pydata/xarray/issues/1194 | 605697466 | MDEyOklzc3VlQ29tbWVudDYwNTY5NzQ2Ng== | 6130352 | 2020-03-29T20:37:29Z | 2020-03-29T20:37:29Z | NONE | I agree, I have this same issue with large genotyping data arrays often containing tiny integers and some degree of missingness in nearly 100% of raw datasets. Are there recommended workarounds now? I am thinking of constantly using Datasets instead of DataArrays with mask arrays to accompany every data array, but I'm not sure if that's the best interim solution. |
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