[USER (data scientist)]: Great, now perform K-means clustering with 4 clusters and add the cluster labels back to the original dataset. Please generate a DataFrame with cluster labels assigned to each customer using K-Means clustering.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd 
from sklearn.cluster import KMeans 
import pickle
from decision_company import read_csv_file, 

# please import the necessary private functions from decision_company first

# Load the dataset 
credit_customers = read_csv_file("credit_customers.csv") 
 
# YOUR SOLUTION BEGIN:
<code1>
[COMPLETE YOUR CODE] 
</code1>
# YOUR SOLUTION END

print("credit_customers:\n", credit_customers) 

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Sure thing! Here's the code to perform K-means clustering and add the cluster labels:
'''
import pandas as pd 
from sklearn.cluster import KMeans 
import pickle
from decision_company import read_csv_file, 

# please import the necessary private functions from decision_company first

# Load the dataset 
credit_customers = read_csv_file("credit_customers.csv") 
 
# YOUR SOLUTION BEGIN:
