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/7539#issuecomment-1438377578,https://api.github.com/repos/pydata/xarray/issues/7539,1438377578,IC_kwDOAMm_X85Vu-Zq,4160723,2023-02-21T12:13:18Z,2023-02-21T12:13:18Z,MEMBER,"In general I also find that `xr.concat` is a powerful feature (incl. auto-alignment and merge options) at the expense that it may sometimes (often?) be hard to reason about. Would it make sense to have a simpler version? To avoid making `xr.concat` signature even more complicated, maybe another top-level function like `xr.concat_noalign`? Or any suggestion in #7045 to deactivate auto-alignment Xarray-wise. Or indeed at least make it clearer in the docs that something like `drop_indexes` or `reset_coords` should be used first in order to skip auto-alignment for some variables.

> I don't really know what I would prefer to happen with the coordinates. I guess to have created a time coordinate of size {new: 2, time: 4, cols: 2}, but then I don't know what that implies for the underlying index. @benbovy do you have any thoughts?

I guess easiest for a concat version with no auto-alignment would be to drop the index when such case happens. (note: one problem in your example is that the Xarray data model still does not allow having a multi-dimensional ""time"" variable with ""time"" as also one of its dimensions, but this could be now relaxed).

I've been also wondering whether some kind of `NDPandasIndex` would make any sense, i.e., a n-d coordinate variable with an internal 1-d (flattened) pandas index and some logic to convert between those n-d vs. 1-d spaces. This is the kind of approach used in xoak for using a kd-tree with coordinates of arbitrary dimensions, where labels in the form of nd-arrays for each coordinate are mapped into the `[n_points, n_coords]` shape (and inversely for getting the integer indices back as nd-arrays). This works well for point-wise indexing, but I doubt it would be very useful beyond that (e.g., slicing, etc.).

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