[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 the code with the output in dataframe type.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd   
import pickle
from decision_company import read_csv_file, create_subplots, df_copy, cast_to_a_dtype, categoricalIndex, categorical_codes, scatter_fig_instance, set_plot_split_title, set_layout, show_plots, save_plot, fetch_column

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

# MY SOLUTION BEGIN:
