Standardizing the happiness dataset

standardized-dataset.py

from sklearn.preprocessing import StandardScaler
std_scaler = StandardScaler()

# fitting the standardscaler on the training set. Then transforming the training set
train_set_std = std_scaler.fit_transform(train_set[:,:2])
train_set_std = np.concatenate((train_set_std, train_set[:,-2:]), axis=1)

# ensuring that we only transform without fitting the validation set
valid_set_std = std_scaler.transform(valid_set[:,:2])
valid_set_std = np.concatenate((valid_set_std, valid_set[:,-2:]), axis=1)

# we repeat the same for test_set as we did for valid_set