issues: 1295939038
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| id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
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| 1295939038 | I_kwDOAMm_X85NPnXe | 6758 | simple groupby_bins 10x slower than numpy | 731499 | closed | 0 | 8 | 2022-07-06T14:36:26Z | 2022-07-07T08:26:26Z | 2022-07-06T17:24:27Z | CONTRIBUTOR | I am finding that groupby_bins is 10x slower than numpy in what I consider to be a simple implementation. In the screenshot below, you can see me opening a netCDF file containing two variables with the same single dimension. One variable is the latitude. I want to aggregate (sum) the other variable in bins of latitude. The xarray approach using groupby_bins takes ~314ms per loop, the numpy approach less than 30ms per loop. I need to do this kind of computation on many more variables, on data spanning several years, and following the xarray approach leads to many more hours of processing :-/ Am I doing something wrong here?
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completed | 13221727 | issue |
