[USER (data scientist)]: Awesome! Now, I want to group the data by player and calculate their average rank and win/loss ratio. Please generate a DataFrame by aggregating unique player data in the ATP tennis dataset, including average rank, average win/loss ratio, and match count.
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(unique_player_data)

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Sure thing! Let's group the DataFrame by player and compute the average rank and win/loss ratio for each unique player. Here's the code for that: 
'''
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:
