NormalizationVsStandarization_3.py

# data standardization with  sklearn
from sklearn.preprocessing import StandardScaler

# copy of datasets
X_train_stand = X_train.copy()
X_test_stand = X_test.copy()

# numerical features
num_cols = ['Item_Weight','Item_Visibility','Item_MRP','Outlet_Establishment_Year']

# apply standardization on numerical features
for i in num_cols:
    
    # fit on training data column
    scale = StandardScaler().fit(X_train_stand[[i]])
    
    # transform the training data column
    X_train_stand[i] = scale.transform(X_train_stand[[i]])
    
    # transform the testing data column
    X_test_stand[i] = scale.transform(X_test_stand[[i]])

Hi, for L14, where did you define X_train_stand before?
I only have X_train and X_test after splitting my df X.

Hi, for L14, where did you define X_train_stand before?
I only have X_train and X_test after splitting my df X.

Hey. So I made a copy of X_train in X_train_stand before standardizing it for comparisons later. However, the line was missing from the gist so I have just added it in.