[USER (data scientist)]: Hey, I've got this ATP tennis dataset, and I'm curious if there's any connection between the court surfaces (hard, clay, grass) and how well the players perform (like their win/loss ratios and rankings). Can you help me out? 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, df_copy, dropna, get_dummies, corr, f_oneway, avg, sem, t_ppf

atp_tennis = read_csv_file('atp_tennis.csv')

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

print(surface_data)

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Absolutely! Let's start by making a DataFrame with the court surfaces, player rankings, and win/loss ratios. Here's the code for that: 

# MY SOLUTION BEGIN:
