I have a dataset like the below:
state year response
1 MA 1 -0.2038564714
2 MA 2 -1.9344440707
3 MA 3 -0.3105101158
4 MA 4 -0.4222270032
5 MA 5 0.6818296904
6 MA 6 1.0094961857
7 MA 7 -0.7261049649
8 MA 8 0.8061088684
9 MA 9 1.4243231097
10 MA 10 -0.7841440048
11 NY 1 -0.6524043665
12 NY 2 0.6507783632
13 NY 3 0.1830479699
14 NY 4 0.5487749604
15 NY 5 1.4046842945
16 NY 6 0.3870831196
17 NY 7 1.0517012702
18 NY 8 0.6229054623
19 NY 9 0.4336203898
20 NY 10 0.3860844382
I want to build a regression model with group by as the "State" variable.
I dont know how to make a group by regression using Random forest regression or gradient boosting algorithms
max_depth = 30
regr_multirf = MultiOutputRegressor(RandomForestRegressor(max_depth=max_depth,
random_state=0))
regr_multirf.fit(X_train, y_train)
Since i am very new to python (my first day of coding), I dont know how to include groupby here.
There was a similar code [here][1] using linear regression. While it has the groupby facility, I dont know whether Randomforest [1]: Python pandas linear regression groupby has this or not. Any help on this will be much appreciated.
Thank you.