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/7456#issuecomment-1460873349,https://api.github.com/repos/pydata/xarray/issues/7456,1460873349,IC_kwDOAMm_X85XEyiF,127195910,2023-03-08T21:04:05Z,2023-06-01T15:42:44Z,NONE,"The xr.Dataset.expand_dims() method can be used to add new dimensions to a dataset. The axis parameter is used to specify where to insert the new dimension in the dataset. However, it's worth noting that the axis parameter only works when expanding along a 1D coordinate, not when expanding along a multi-dimensional array.
Here's an example to illustrate how to use the axis parameter to expand a dataset along a 1D coordinate:
import xarray as xr
# create a sample dataset
data = xr.DataArray([[1, 2], [3, 4]], dims=('x', 'y'))
ds = xr.Dataset({'foo': data})
# add a new dimension along the 'x' coordinate using the 'axis' parameter
ds_expanded = ds.expand_dims({'z': [1]}, axis='x')
In this example, we create a 2D array with dimensions x and y, and then add a new dimension along the x coordinate using the axis='x' parameter.
However, if you try to use the axis parameter to expand a dataset along a multi-dimensional array, you may encounter an error. This is because expanding along a multi-dimensional array would result in a dataset with non-unique dimension names, which is not allowed in xarray.
Here's an example to illustrate this issue:
import xarray as xr
# create a sample dataset with a 2D array
data = xr.DataArray([[1, 2], [3, 4]], dims=('x', 'y'))
ds = xr.Dataset({'foo': data})
# add a new dimension along the 'x' and 'y' coordinates using the 'axis' parameter
ds_expanded = ds.expand_dims({'z': [1]}, axis=('x', 'y'))
In this example, we try to use the axis=('x', 'y') parameter to add a new dimension along both the x and y coordinates. However, this results in a ValueError because the resulting dataset would have non-unique dimension names.
To add a new dimension along a multi-dimensional array, you can instead use the xr.concat() function to concatenate the dataset with a new data array along the desired dimension:
import xarray as xr
# create a sample dataset with a 2D array
data = xr.DataArray([[1, 2], [3, 4]], dims=('x', 'y'))
ds = xr.Dataset({'foo': data})
# add a new dimension along the 'x' and 'y' coordinates using xr.concat
ds_expanded = xr.concat([ds, xr.DataArray([1], dims=('z'))], dim='z')
In this example, we use the xr.concat() function to concatenate the original dataset with a new data array that has a single value along the new dimension z. The dim='z' parameter is used to specify that the new dimension should be named z.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1548355645
https://github.com/pydata/xarray/issues/7456#issuecomment-1397549856,https://api.github.com/repos/pydata/xarray/issues/7456,1397549856,IC_kwDOAMm_X85TTOsg,45972964,2023-01-19T20:21:12Z,2023-01-19T23:54:29Z,NONE,"EDIT: Lots of confusion below about nothing, plz disregard
Okay, regardless of expected behavior here, my particular use-case *requires* that I transpose these dimensions. Can someone show me a way to do this? I tried to explain the xarray point of view to Keras, but Keras is really not interested ;)
I tried something like `ds.expand_dims(""sample"").transpose('sample','nlat','nlon')` to complete futility, probably something to do with the `Frozen` stuff if I had to guess.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1548355645
https://github.com/pydata/xarray/issues/7456#issuecomment-1397648400,https://api.github.com/repos/pydata/xarray/issues/7456,1397648400,IC_kwDOAMm_X85TTmwQ,45972964,2023-01-19T21:45:24Z,2023-01-19T21:45:24Z,NONE,"I was thinking something like this:
```
da = xr.DataArray([[1,2,3],[4,5,6],[7,8,9]], coords={'a':[1,2,3], 'b':[1,2,3]})
ds = xr.Dataset({'da':da})
ds1 = ds.expand_dims('yomama', axis=0)
print(ds1[0].dims)
ds2 = ds.expand_dims('yomama', axis=2)
print(ds2[0].dims)
```
...but this throws an error (like it should). I think I must be reading my code wrong lol","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1548355645
https://github.com/pydata/xarray/issues/7456#issuecomment-1397633052,https://api.github.com/repos/pydata/xarray/issues/7456,1397633052,IC_kwDOAMm_X85TTjAc,45972964,2023-01-19T21:29:10Z,2023-01-19T21:29:10Z,NONE,"Okay I think I get the philosophy now. However, indexing a DataSet with an integer actually *does* work. If performance is the goal, shouldn't something like `ds[0]` throw a warning or an error?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1548355645
https://github.com/pydata/xarray/issues/7456#issuecomment-1397588476,https://api.github.com/repos/pydata/xarray/issues/7456,1397588476,IC_kwDOAMm_X85TTYH8,45972964,2023-01-19T20:49:52Z,2023-01-19T20:53:29Z,NONE,"Nvm, my use case isn't what I thought it was, but I'll push the issue a bit.
So I'm not disputing anything about what these functions actually do now, the issue I have is that the functions here treat the dimension order of a DataSet as if it's arbitrary, but calling `[]` on a DataSet slices it in a decidedly non-arbitrary way. It turns out that `[]` actually *does* care about which axis you select if you call `expand_dims` first, and you index with an integer like `[0]`. I think this inconsistency is what's confusing to me atm.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1548355645
https://github.com/pydata/xarray/issues/7456#issuecomment-1397408991,https://api.github.com/repos/pydata/xarray/issues/7456,1397408991,IC_kwDOAMm_X85TSsTf,45972964,2023-01-19T18:13:16Z,2023-01-19T18:13:16Z,NONE,"Yeah, I could put something together. It'll probably have to wait until next week though.","{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 1, ""rocket"": 0, ""eyes"": 0}",,1548355645
https://github.com/pydata/xarray/issues/7456#issuecomment-1397292416,https://api.github.com/repos/pydata/xarray/issues/7456,1397292416,IC_kwDOAMm_X85TSP2A,45972964,2023-01-19T16:49:58Z,2023-01-19T16:52:33Z,NONE,"I mean that's fine, but in that case, the documentation is very misleading ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1548355645