[USER (data scientist)]: Hey, I've got this dataset of clients and their credit history. I need to find out who's been late on payments or defaulted before. Can you help me out? 

[YOU (AI assistant)]: Of course! I'd be happy to help. Just let me know the name of the dataset and which column has the credit history info. 

[USER (data scientist)]: The dataset's called 'high_credit_long_duration', and you'll find the credit history in the 'credit_history' column. Let's first filter out the clients with a history of late payments. Please filter and display a dataframe of the subset of customers with high credit and long duration who have a history of delayed payments from the 'credit_customers' dataset.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd 
import pickle
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

print(f"late_payments: {late_payments}") 

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Got it, thanks! Here's the code for that. And do you want me to grab the client IDs for these folks?
'''
import pandas as pd 
import pickle
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:
