[USER (data scientist)]: I want to do K-means clustering with 4 clusters. Can you show me how? Please generate a NumPy array of cluster labels from K-means clustering on the scaled dataset.
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("cluster_labels:\n", cluster_labels) 

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Of course! You can perform K-means clustering with 4 clusters using proper functions from decision_company like this:
'''
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:
