[USER (data scientist)]: Are there any significant differences in credit amount between younger customers and those with a good credit history compared to other customer segments? Please provide statistical tests (e.g., t-test or ANOVA) to compare credit amounts between the specified customer segments. 
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd  
import scipy.stats as stats  
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"F-statistic: {f_statistic}, P-value: {p_value}") 

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

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

---END CODE TEMPLATE---

[YOU (AI assistant)]:No problem! We can modify the question to focus on the relationship between age, credit history, and credit amount. To determine if there are any significant differences in credit amount between younger customers (aged 18-35) with a good credit history and other customer segments, we can perform an ANOVA test. Here's the code to perform the test:
'''
import pandas as pd  
import scipy.stats as stats  
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:
