Preprocessing.py

#Filling Nulls/Nans
train.fillna('NAN', inplace = True)

#Label Encoding
from sklearn.preprocessing import LabelEncoder
le_c = LabelEncoder().fit(unique_cuisines)
train['Cuisines'] = le_l.transform(train['Cuisines'])

#Scaling
cols = [list of columns to apply standard scaler]
from sklearn.preprocessing import StandardScaler
ss = StandardScaler()
train[cols] = ss.fit_transform(train_sample[cols])