[USER (data scientist)]: I will generate the code to summarize the key characteristics of each target customer segment in the credit_customers dataset. The result type will be a summary of key characteristics for each target customer segment. Specifically, you can generate a summary dictionary to analyze the key characteristics of target customer segments based on their 'age', 'credit_amount', 'employment', 'savings_status', and 'credit_history' within the 'credit_customers' dataset after performing K-means clustering.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd  
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("summary:\n", summary)  

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Sure, I can help you:
'''
import pandas as pd  
import pickle
  
# Load the dataset  
credit_customers = pd.read_csv("credit_customers.csv")  
  
# YOUR SOLUTION BEGIN:
