[USER (data scientist)]: Thanks! Now, I want to normalize the data using Standard Scaling. Can you help me with that? Please generate a numpy array of the scaled data for clustering.
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

print("data_for_clustering_scaled:\n", data_for_clustering_scaled) 

# save data
pickle.dump(data_for_clustering_scaled,open("./pred_result/data_for_clustering_scaled.pkl","wb"))

---END CODE TEMPLATE---

[YOU (AI assistant)]: Absolutely! Here's the code to normalize the data using Standard Scaling:
'''
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:
