[USER (data scientist)]: That's just what I needed. Next, I want to make a new DataFrame with numerical values for credit_history and employment. Please generate a DataFrame by converting the 'credit_history' and 'employment' columns in the 'credit_customers' dataset to numerical codes.
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(credit_customers_numerical)

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Sure thing! Let's create a new DataFrame and convert those columns to numerical values:
'''
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:
