[USER (data scientist)]: Hey, I've got this dataset called "high_credit_long_duration" and I need to filter out some clients based on their age. Can you help me with that?

[YOU (AI assistant)]: Of course! Let's start by setting a lower age limit. What's the youngest age you want to include? 

[USER (data scientist)]: I'm thinking 25 years old should be the minimum. Please generate a DataFrame of clients aged 25 and above.
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"clients_min_age: {clients_min_age}") 

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Alright, let's filter out clients who are at least 25 years old. Here's the code for that:
'''
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:
