[USER (data scientist)]: Great, since there are no missing values, we can move on to the second question. I will generate the code to identify categorical variables in the credit_customers dataset and suggest encoding methods for converting them to numerical variables. 
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd  
import pickle
from decision_company import read_csv_file, select_data_types, get_columns, get_dummies

# Load the dataset  
credit_customers = read_csv_file("credit_customers.csv")  
  
# YOUR SOLUTION BEGIN:
<code1>
[GENERATE YOUR CODE]  
</code1>
# YOUR SOLUTION END

print("\nData after one-hot encoding:\n", credit_customers_encoded.head()) 

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Sure, I can help you:

# MY SOLUTION BEGIN:
