[USER (data scientist)]: Let's go with K-means clustering. 

[YOU (AI assistant)]: Sounds good! How many clusters are you aiming for? 

[USER (data scientist)]: I think 4 clusters should do the trick. Please generate a NumPy array of cluster labels from the KMeans algorithm applied to the scaled dataset.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd 
from sklearn.cluster import KMeans 
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("cluster_labels:\n", cluster_labels) 

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Alright, let's perform K-means clustering with 4 clusters:
'''
import pandas as pd 
from sklearn.cluster import KMeans 
import pickle
 
# Load the dataset 
credit_customers = pd.read_csv("credit_customers.csv") 
 
# YOUR SOLUTION BEGIN:
