[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 
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')

create_figure(figsize=(12, 6))

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

# save data
save_plot("./pred_result/barplot.png")
show_plot() 

---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 
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')

create_figure(figsize=(12, 6))

# YOUR SOLUTION BEGIN:
