issues: 264582338
This data as json
| 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 264582338 | MDU6SXNzdWUyNjQ1ODIzMzg= | 1626 | Structured numpy arrays, xarray and netCDF(4) | 4489333 | open | 0 | 6 | 2017-10-11T13:16:04Z | 2022-04-28T13:51:20Z | NONE | I'm trying to use xarray as the underlying container for some data processing tasks. Part of the pipeline includes processing from non-standard/easily readable formats (e.g. ROS messages) to standard formats, e.g. netCDF(4). The data I tend to be working on is time series data that is structured, which maps pretty well to structured numpy arrays using dtype manipulations. And xarray lightly wraps numpy, and provides netCDF as a backend. However, the xarray implementation doesn't really expose this capability, supported in netCDF as 'compound data types', and in fact it fails when you try and write such a So the question is, is this a reasonable feature/expectation from xarray (and thus you're receptive to contributions), or is this outside the goal/purpose (I should roll my own/use pandas/etc)? |
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13221727 | issue |