[USER (data scientist)]: Lastly, I want to perform some statistical tests to see if there's a significant difference in win/loss ratios across surface types for each ranking group. Please generate the code with the output in dictionary type.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd
import numpy as np
from scipy import stats 
import pickle
from decision_company import read_csv_file, create_dataframe, df_copy, concatenate_objects, bind_dataframe, aggregate_grouped_data, positive_infinity, make_bins, join_dataframes, create_figure, create_barplot, set_plot_title, set_yaxis_label, show_plots, join_dataframes, anova_test, dropna

atp_tennis = read_csv_file('atp_tennis.csv')

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

print(anova_results)

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: We can perform an ANOVA test for each ranking group to test for significant differences. Let's run the test and print the p-values to check for significant differences in win/loss ratios across surface types. Here's the code for that: 

# MY SOLUTION BEGIN:
