[USER (data scientist)]: Fantastic! Lastly, I'd like to see the credit history distribution of our customers. Please generate and display a series of the distribution of credit history values in the 'credit_customers' dataset.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd 
import pickle
 
# Load the dataset 
credit_customers = pd.read_csv("credit_customers.csv") 

# YOUR SOLUTION BEGIN:
<code1>
[COMPLETE YOUR CODE] 
</code1>
# YOUR SOLUTION END

print("\nCredit History Distribution:") 
print(credit_history_counts) 

# save data
pickle.dump(credit_history_counts,open("./pred_result/credit_history_counts.pkl","wb"))

---END CODE TEMPLATE---

[YOU (AI assistant)]: No problem! You can use the "value_counts()" function to get the credit history distribution. Here's the code:
'''
import pandas as pd 
import pickle
 
# Load the dataset 
credit_customers = pd.read_csv("credit_customers.csv") 

# YOUR SOLUTION BEGIN:
