fix: across handles sql grouped; handles pandas mutate with aggs

[machow]

This PR provides two fixes for across()

• fix(sql): across() now currently sets the OVER clause when LazyTbl is grouped.
• fix(pandas): across() now correctly handles aggregates inside a mutate. Previously, it was screwing up the placement of the result by assigning using the index, and not broadcasting.

from siuba.data import cars
from siuba import across, Fx, mutate, head

cars.groupby("cyl") >> mutate(across(_[_.hp, _.mpg], Fx.mean())) >> head()

   cyl        mpg          hp
0    6  19.742857  122.285714
1    6  19.742857  122.285714
2    4  26.663636   82.636364
3    6  19.742857  122.285714
4    8  15.100000  209.214286