The following seems to happen on all transform groupby kernels:

df = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
df.groupby([1, 1], axis=1).transform("shift")

results in ValueError: Length mismatch: Expected axis has 2 elements, new values have 3 elements.

I think the issue is in pandas.core.groupby.generic._wrap_transformed_output; this method does not take into account `s

The documentation in the Joins section https://docs.dask.org/en/latest/dataframe-joins.html has code blocks but they aren't interactive and therefore not as useful.

I think the documentation would benefit from an interactive example with use of real data (or data from the demo API).

I had a quick rummage of the tutorial (h

Improve readability of thread id based branches by giving them more descriptive names.

e.g.

if (!t) // is actually a t == 0

and

https://github.com/rapidsai/cudf/blob/57ef76927373d7260b6a0eda781e59a4c563d36e/cpp/src/io/statistics/column_stats.cu#L285
Is actually a lane_id == 0
As demonstrated in rapidsai/cudf#6241 (comment), pr

Support Series.median()

What happened:
xr.DataArray([1], coords=[('onecoord', [2])]).sel(onecoord=2).to_dataframe(name='name') raise an exception ValueError: no valid index for a 0-dimensional object

What you expected to happen:

the same behavior as: xr.DataArray([1], coords=[('onecoord', [2])]).to_dataframe(name='name')

Anything else we need to know?:

I see that the array after the select