issue_comments: 379937531
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/1603#issuecomment-379937531 | https://api.github.com/repos/pydata/xarray/issues/1603 | 379937531 | MDEyOklzc3VlQ29tbWVudDM3OTkzNzUzMQ== | 1217238 | 2018-04-10T00:42:19Z | 2018-04-10T00:42:19Z | MEMBER | @fujiisoup Yes, we certainly could add a "N-dimensional index", even if it has no function other than a placeholder to mark a variable as an index. This would let us restore index state after selecting/concatenating along a dimension. However, I'm not sure it would be a satisfactory solution. If we keep these indexes around like coordinates, we could end up with scalar coordinates from different dimensions. Then it's still not clear how they should stack up in the final result -- we would have the same issue we currently have with concatenating coordinates. The other concern is that existence and behavior of scalar/N-dimensional indexes could be a surprising. What does it mean to index an N-dimensional index? This operations probably cannot be supported in a sensible way, or at least not without significant effort. |
{
"total_count": 0,
"+1": 0,
"-1": 0,
"laugh": 0,
"hooray": 0,
"confused": 0,
"heart": 0,
"rocket": 0,
"eyes": 0
} |
262642978 |