[USER (data scientist)]:For the sixth question, we want to find the count of clients in the final filtered dataset who reside in rented or owned housing, excluding those living rent-free. Please provide the result type as a count of clients residing in rented or owned housing. Specifically, you can generate a dataframe filtering clients in the 'credit_customers' dataset who reside in rented or owned housing, and calculate the count of these clients, saving the result as a pickle file.
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_2.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:
