import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.feature_selection import RFE
from sklearn.linear_model import LogisticRegression

full_df = pd.read_csv('data.csv')

x = full_df.iloc[:,:-1]
y = full_df.iloc[:,-1]

x_train, x_test, y_train, y_test = train_test_split(x, y, test_size = 0.3, random_state = 42)

model = LogisticRegression(solver ='lbfgs')

for i in range(1,120):

    rfe = RFE(model, i)
    fit = rfe.fit(x_train, y_train)
    acc = fit.score(x_test, y_test)

    print(acc)
    print(fit.support_)