[FEA] Support passing arguments to functions in groupby apply

[beckernick]

In pandas , I can pass arguments to a function used with groupby.apply. This is currently used internally to the Dask codebase (#10294) and also exposed in the public interface.

import dask.dataframe as dd
import pandas as pd
import dask_cudf
import cudf
​
df = pd.DataFrame({
    "a": [0,0,1,0,0,1,1,1,1,1],
    "b": [0,0.3,0,-4,0,-3,1,1,11,1],
    "c": [19,0,30,0,0,1,41,1,1,1],
})
gdf = cudf.from_pandas(df)
ddf = dd.from_pandas(df, 2)
gddf = dask_cudf.from_dask_dataframe(ddf)
​
def func(x, delta):
    return x + delta
​
print(df.groupby("a").b.apply(func, 3))
print(ddf.groupby("a").b.apply(func, 3).compute())
0     3.0
1     3.3
2     3.0
3    -1.0
4     3.0
5     0.0
6     4.0
7     4.0
8    14.0
9     4.0
Name: b, dtype: float64
2     3.0
5     0.0
6     4.0
7     4.0
8    14.0
9     4.0
0     3.0
1     3.3
3    -1.0
4     3.0
Name: b, dtype: float64
/tmp/ipykernel_78541/1691277680.py:19: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.
  Before: .apply(func)
  After:  .apply(func, meta={'x': 'f8', 'y': 'f8'}) for dataframe result
  or:     .apply(func, meta=('x', 'f8'))            for series result
  print(ddf.groupby("a").b.apply(func, 3).compute())

[github-actions]

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