[BUG] GroupedTransformer can't deal with transformers that use `y`

Hi! First of all thanks for your package, it’s awesome! (Same as calmcode and other resources you built).

I’m trying to perform a LeaveOneOutEncoder transformation for each group of my dataset and I think it’s not possible (or I can’t get it), the problem is that within sklego/meta/grouped_transformer.py the fit is called without y and it throws an error: TypeError: fit() missing 1 required positional argument: 'y'.

I post here a dummy example that has the same functionality that the thing I’m trying to do in my code:

import pandas as pd
import numpy as np

from sklego.datasets import load_heroes
from sklego.meta import GroupedTransformer
from category_encoders import LeaveOneOutEncoder


df_heroes = load_heroes(as_frame=True).replace([np.inf, -np.inf], np.nan).dropna()

# Dummy example
X = df_heroes[['attack_type', 'health', 'attack_spd']]
y = df_heroes['attack']

GroupedTransformer(LeaveOneOutEncoder(), groups=['attack_type']).fit_transform(X, y)

Thansk in advance!

[MBrouns]

It looks like the problem appears here: https://github.com/koaning/scikit-lego/blob/main/sklego/meta/grouped_transformer.py#L90

for all the estimators fitted on the subgroups we pass y as far as I can tell, but the global fallback model is fitted without it. The bit you linked @koaning is in the transform step and although the LeaveOneOutEncoder does use y during transform as well I would expect a different error.

I’m all OK for making the changes to both parts, but I would like to test whether passing along y will actually work for the transform step. I remember from building the TrainOnlyTransformerMixin it was not very clear when y would get passed along to the transform step when running from a pipeline and when it wouldnt.

[sergiocalde94]

Do you need any help with this issue? Is it something missed on my part?