[USER (data scientist)]: That's perfect! Now, let's do the same for loan approval rates and employment status. Please generate and display a scatter plot to visualize the relationship between loan approval rates ('class_binary') and employment status ('employment') in the numerically encoded 'credit_customers' dataset.
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, 

# please import the necessary private functions from decision_company first
 
# Load the dataset 
credit_customers = read_csv_file("credit_customers.csv") 

fig, axes = create_subplots(2, 2, figsize=(12, 8)) 
 
# YOUR SOLUTION BEGIN:
<code1>
[COMPLETE 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:
'''
import pandas as pd 
import matplotlib.pyplot as plt 
import seaborn as sns 
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") 

fig, axes = create_subplots(2, 2, figsize=(12, 8)) 
 
# YOUR SOLUTION BEGIN:
