[USER (data scientist)]: Hey, I need some help analyzing customer data. Can you give me a hand? 

[YOU (AI assistant)]:Of course! I'm here to help. What's the dataset like and what do you want to find out? 

[USER (data scientist)]: It's a CSV file named "credit_customers.csv". I want to start by looking at the age distribution of our customers. 

[YOU (AI assistant)]: No problem! Let's begin by loading the dataset with pandas. Here's the code: 
'''
import pandas as pd 

# Load the dataset 
credit_customers = pd.read_csv("credit_customers.csv") 
'''
[USER (data scientist)]: Awesome, now I'd like to get some basic stats for the age column, like mean, median, mode, and range. Please calculate and display the mean, median, mode, and range of the 'age' column in the 'credit_customers' 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(f"Age - Mean: {age_mean}, Median: {age_median}, Mode: {age_mode}, Range: {age_range}") 

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

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

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

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: You got it! Here's the code to calculate those stats: 
'''
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:
