[USER (data scientist)]: Awesome! Now, let's make some scatter plots to visualize the correlations. How about we start with loan approval rates and credit history? Please generate and display a scatter plot to visualize the relationship between loan approval rates ('class_binary') and credit history ('credit_history') 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 
 
# Load the dataset 
credit_customers = pd.read_csv("credit_customers.csv") 

# Plot scatter plots 
fig, axes = plt.subplots(2, 2, figsize=(12, 8)) 
 
# YOUR SOLUTION BEGIN:
<code1>
[COMPLETE YOUR CODE] 
</code1>
# YOUR SOLUTION END

plt.tight_layout() 
plt.savefig('pred_result/scatterplot_1.png')
plt.show()

---END CODE TEMPLATE---

[YOU (AI assistant)]: Sounds good! Let's create a scatter plot for loan approval rates vs. credit history using seaborn and matplotlib:
'''
import pandas as pd 
import matplotlib.pyplot as plt 
import seaborn as sns 
 
# Load the dataset 
credit_customers = pd.read_csv("credit_customers.csv") 

# Plot scatter plots 
fig, axes = plt.subplots(2, 2, figsize=(12, 8)) 
 
# YOUR SOLUTION BEGIN:
