issue_comments: 304778433
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/pull/1426#issuecomment-304778433 | https://api.github.com/repos/pydata/xarray/issues/1426 | 304778433 | MDEyOklzc3VlQ29tbWVudDMwNDc3ODQzMw== | 1217238 | 2017-05-30T05:29:11Z | 2017-05-30T05:29:11Z | MEMBER | Sorry for the delay getting back to you here -- I'm still thinking through the implications of this change. This does make the handling of However, taking a step back, I wonder if this is the right approach. In many ways, structured dtypes are similar to xarray's existing data structures, so supporting them fully means a lot of duplicated functionality. MultiIndexes (especially with scalars) should work similarly to separate variables, but they are implemented very differently under the hood (all the data lives in one variable). (See https://github.com/pandas-dev/pandas/issues/3443 for related discussion about pandas and why it doesn't support structured dtypes.) It occurs to me that if we had full support for indexing on coordinate levels, we might not need a notion of a "MultiIndex" in the public API at all. To make this more concrete, what if this was the Pandas has CC @benbovy |
{ "total_count": 2, "+1": 2, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
231308952 |