[USER (data scientist)]: Hey, I've got this dataset of clients with stable jobs, and I wanna figure out some common traits of those who could benefit from debt consolidation. Can you help me out? 

[YOU (AI assistant)]: Absolutely! Let's start by finding the average credit amount for these clients. What's the name of the DataFrame with the data? 

[USER (data scientist)]: Oh, it's called 'stable_employment'. Please calculate and save the average credit amount as a numerical value in a pickle file.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd 
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(f"average_credit_amount: {average_credit_amount}") 

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Cool, let's calculate the average credit amount for the clients in 'stable_employment'. Here's the code:
'''
import pandas as pd 
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:
