[USER (data scientist)]:For the fourth question, we want to find the count of clients aged between 25 and 55 in the filtered dataset from the first step. Please provide the result type as a count of clients aged between 25 and 55. Specifically, you can generate a count (integer) and save it as a pickle file by filtering the 'high_credit_long_duration' dataframe for clients aged between 25 and 55 from the 'credit_customers.csv' 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(result_count)

# save data
pickle.dump(result_count,open("./pred_result/result_count_1.pkl","wb"))

---END CODE TEMPLATE---

[YOU (AI assistant)]: Sure, I can help you with 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:
