[USER (data scientist)]: Cool! Can we visualize this data with a bar chart comparing win/loss ratios across ranking groups and surface types? Please generate a bar plot comparing the average win/loss ratios by surface type and ranking group in the ATP tennis dataset.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd
import numpy as np 
import matplotlib.pyplot as plt 
import seaborn as sns 

atp_tennis = pd.read_csv('atp_tennis.csv')

plt.figure(figsize=(12, 6)) 

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

plt.savefig("./pred_result/barplot.png")
plt.show() 

---END CODE TEMPLATE---

[YOU (AI assistant)]: Definitely! Let's create a bar chart using seaborn and matplotlib. Here's the code for that: 
'''
import pandas as pd
import numpy as np 
import matplotlib.pyplot as plt 
import seaborn as sns 

atp_tennis = pd.read_csv('atp_tennis.csv')

plt.figure(figsize=(12, 6)) 

# YOUR SOLUTION BEGIN:
