import pandas as pd
from sklearn.model_selection import train_test_split

from sklearn.preprocessing import StandardScaler

data = pd.read_csv('/datasets/travel_insurance.csv')

target = data['Claim']
features = data.drop('Claim', axis=1)
features_train, features_valid, target_train, target_valid = train_test_split(
    features, target, test_size=0.25, random_state=12345)

numeric = ['Duration', 'Net Sales', 'Commision (in value)', 'Age']

scaler = StandardScaler()
scaler.fit(features_train[numeric])

features_train[numeric] = scaler.transform(features_train[numeric])


print(features_train.head())