[USER (data scientist)]: Next up, let's make a correlation matrix for the court surfaces, average player rankings, and average win/loss ratios. Please generate a DataFrame that displays the correlation matrix for selected columns, including surface types and average statistics, in a subset of the ATP tennis 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

atp_tennis = read_csv_file('atp_tennis.csv')

# YOUR SOLUTION BEGIN:
<code1>
[COMPLETE YOUR CODE] 
</code1>
# YOUR SOLUTION END

print(corr_matrix)

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Here's the code to create that correlation matrix: 
'''
import pandas as pd
import pickle
from decision_company import read_csv_file,

# please import the necessary private functions from decision_company first

atp_tennis = read_csv_file('atp_tennis.csv')

# YOUR SOLUTION BEGIN:
