feature selection sequentialfeatureselector complete code

#Import Libraries
import numpy as np
import pandas as pd
from sklearn.feature_selection import SequentialFeatureSelector
from sklearn.linear_model import LogisticRegression


# Data Processing
df=pd.read_csv("https://archive.ics.uci.edu/ml/machine-learning-databases/00537/sobar-72.csv")
y=df.pop('ca_cervix')


#Feature Selection
model = LogisticRegression(max_iter=3000).fit(df, y)
forward_sfs = SequentialFeatureSelector(model, n_features_to_select=10, direction="forward").fit(df, y)
df.columns[forward_sfs.get_support()]