[USER (data scientist)]: Hey, I have this ATP tennis dataset and I want to analyze how different surface types affect player performance across various player ranking groups. Let's start by creating a new DataFrame with separate rows for each player. Please generate a DataFrame by combining player-specific data from two sets of columns in 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(player_data)

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Great! Let's create a new DataFrame with those columns and add data for both Player_1 and Player_2. 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:
