[USER (data scientist)]: Awesome, now let's sift out the customers who have a solid credit history. We can consider 'existing paid', 'no credits/all paid', and 'all paid' as indicators of good credit history. 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, access_dataframe_loc, access_dataframe_loc, logical_and, filter_by_condition, check_elements_in_list, fetch_column, f_oneway

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

print(good_credit_history)  

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: To filter customers with good credit history, we can use the following code:

# MY SOLUTION BEGIN:
