[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 generate the code with the output in dataframe type.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd  
import pickle
from decision_company import read_csv_file, filter_by_value, fetch_index, convert_to_list

# Load the dataset  
credit_customers = read_csv_file("credit_customers.csv")  
  
# YOUR SOLUTION BEGIN:
<code1>
[GENERATE 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?

# MY SOLUTION BEGIN:
