issue_comments: 705098106
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/3332#issuecomment-705098106 | https://api.github.com/repos/pydata/xarray/issues/3332 | 705098106 | MDEyOklzc3VlQ29tbWVudDcwNTA5ODEwNg== | 1217238 | 2020-10-07T17:54:32Z | 2020-10-07T17:54:32Z | MEMBER | The loop via slicing is not a terrible option. The trick construct() uses with views only really makes sense with NumPy arrays, not with dask. There are also true streaming moving window algorithms that work very well for computing various statistics (e.g., mean and variance). These are implemented in bottleneck (e.g., |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
496809167 |