[USER (data scientist)]:Alright. Can you whip up some bar charts that show loan approval rates, you know, when the 'class' column is marked as 'good', for each credit history category, employment status, the middle-age group from 40 to 59 years old, and credit amount range? Don't forget, we're using bins of 2000 for the credit amounts. Specifically, you can generate a series of DataFrame visualizations to display the relationship between loan approval rates and various factors such as credit history, employment status, age group (specifically 40-59), and credit amount range in the 'credit_customers' dataset.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd  
import matplotlib.pyplot as plt  
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

# Plot bar charts  
fig, axes = create_subplots(2, 2, figsize=(12, 8))  
  
# YOUR SOLUTION BEGIN:
<code2>
[COMPLETE YOUR CODE]
</code2>
# YOUR SOLUTION END

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

---END CODE TEMPLATE---

[YOU (AI assistant)]:Sure, I can help you with that. To generate bar charts for loan approval rates based on the specified columns and conditions, you can use the following code:
'''
import pandas as pd  
import matplotlib.pyplot as plt  
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:
