[USER (data scientist)]: Hey, I've got this dataset with original and updated odds for two players in a tournament. I want to see how the competitiveness of the tournament changes with the updated odds. Can you help me out? 

[YOU (AI assistant)]: Absolutely! Let's break it down step by step. First, we need to find the difference in odds for each match. Is your dataset in a pandas DataFrame? 

[USER (data scientist)]: Yep, it's in a DataFrame called updated_odds_df. Please generate the code with the output in dataframe type.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd
import numpy as np
import pickle
from decision_company import read_csv_file, create_figure, set_plot_ylabel, set_plot_xlabel, set_plot_title, show_plots, save_plot, draw_lineplot, plot_kde, add_legend, draw_countplot

# Load the dataset 
atp_tennis = read_csv_file('atp_tennis.csv')

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

print(updated_odds_df)

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Cool! Let's calculate the difference in odds for each match. Here's the code. Now that we've got the difference in odds, let's visualize the data. What kind of plot would you like to see for the distribution of original and updated odds for both players? 

# MY SOLUTION BEGIN:
