[USER (data scientist)]: Thanks a bunch! Now, I'm wondering what encoding methods I should use for these nominal categorical variables. Any suggestions? Please generate a Series listing the nominal categorical columns suitable for one-hot encoding in the dataset.
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("nominal_categorical_columns:\n", nominal_categorical_columns) 

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Absolutely! I suggest using one-hot encoding for nominal categorical variables. Here's the code to display the suggested encoding method:
'''
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:
