[USER (data scientist)]: And if I do need to normalize it, how can I use Standard Scaling for that? Please generate a DataFrame of normalized data using Standard Scaling.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd 
from sklearn.preprocessing import StandardScaler 
import pickle
 
# Load the dataset 
credit_customers = pd.read_csv("credit_customers.csv") 
 
# YOUR SOLUTION BEGIN:
<code1>
[COMPLETE YOUR CODE] 
</code1>
# YOUR SOLUTION END

if normalization_needed: 
 print("credit_customers_normalized:\n", credit_customers_normalized) 
 
# save data
pickle.dump(credit_customers_normalized,open("./pred_result/credit_customers_normalized.pkl","wb"))

---END CODE TEMPLATE---

[YOU (AI assistant)]: If normalization is needed, you can use the 'StandardScaler' from the 'sklearn.preprocessing' module. Here's the code to do that:
'''
import pandas as pd 
from sklearn.preprocessing import StandardScaler 
import pickle
 
# Load the dataset 
credit_customers = pd.read_csv("credit_customers.csv") 
 
# YOUR SOLUTION BEGIN:
