[USER (data scientist)]: That's perfect! Now, let's do the same for loan approval rates and employment status. Please generate the code with the output in plot type.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd   
import matplotlib.pyplot as plt   
import seaborn as sns 
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")   

fig, axes = create_subplots(2, 2, figsize=(12, 8))  
  
# YOUR SOLUTION BEGIN:
<code1>
[GENERATE YOUR CODE]  
</code1>
# YOUR SOLUTION END

# save data
save_plot('pred_result/scatterplot_2.png')
show_plots()

---END CODE TEMPLATE---

[YOU (AI assistant)]: You got it! Here's the scatter plot for loan approval rates vs. employment status:

# MY SOLUTION BEGIN:
