[USER (data scientist)]: I've got this dataset called "high_credit_long_duration" and I need to find clients with multiple existing credits and high installment commitments. Can you help me out?

[YOU (AI assistant)]: Sure, I can definitely help you with that. Can you provide me with some more details about the dataset you're working with? What kind of information does it contain, and what format is it in?

[USER (data scientist)]: We also assume that `high` installment commitments are those above the `median` value of the 'installment_commitment' column. 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, calculate_median, filter_by_condition, create_condition, logical_and, fetch_index, convert_to_list, fetch_column

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

print(f"multiple_credits_high_commitment: {multiple_credits_high_commitment}")  

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Understood. Here's how you can find clients with multiple existing credits and high installment commitments:

# MY SOLUTION BEGIN:
