X = df.drop(target_class_name, axis=1)
y = df[target_class_name]

# split into train and test set
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# Note optionally convert the pandas dataframe into a numpy array using to_numpy if you have a big data
# and want to model faster. Otherwise it doesnt matter which data structure you use