Individual User Windfall: Facebook, Inc. Consumer Privacy User Profile Litigation

import pandas as pd
import numpy as np

users = 240000000
penalty = 725000000
avail_money = 543700000
fb_val = 544750000000

penalty_pct = (penalty/fb_val) * 100

penalty_pct

avail_money/penalty * 100

def payout(pct_users):
    if pct_users == 0:
        return 0
    
    user_claims = (pct_users / 100) * users
    
    return np.around(avail_money/user_claims, 2)

def formatted_money(x):
    return "${:.2f}".format(x)

def tot_users(pct_users):
    return (pct_users / 100) * users

print(f'Total Users: {tot_users(1)}')

tiers = [(x, tot_users(x), payout(x)) for x in range(0, 110, 10)]

df = pd.DataFrame(tiers, columns=['pct_users_filed', 'qty_users_filed', 'payout_per_user'])

df

import matplotlib.pyplot as plt
import matplotlib.ticker as ticker

fig, ax = plt.subplots(figsize=(10, 8), dpi=100)

# Calculate size of markers based on payout per user
sizes = 400 * np.sqrt(df['payout_per_user']) / np.max(np.sqrt(df['payout_per_user']))

# Set the y-axis tick format to include two decimal places
plt.gca().yaxis.set_major_formatter(ticker.FormatStrFormatter('%.2f'))

# Create scatter plot
plt.scatter(df['pct_users_filed'], df['payout_per_user'], 
            c=df['qty_users_filed'], cmap='plasma', alpha=0.8, edgecolor='black', s=sizes)

# Add labels and title
plt.xlabel('% Of American Users Filing A Claim', fontsize=12, labelpad=15)
plt.ylabel('Payout Per User ($)', fontsize=12, labelpad=15)
plt.title('Facebook Class Action Lawsuit Payout (By User Participation)', fontsize=14, pad=20)

# Format ytick labels
# ytick_labels = ['{:.2f}'.format(y) for y in ax.get_yticks()]
# ax.set_yticklabels(ytick_labels)

# Set tick label font size
plt.xticks(fontsize=10)
plt.yticks(fontsize=10)

# Add colorbar
cbar = plt.colorbar()
cbar.set_ticks([0, 50000000, 100000000, 150000000, 200000000, 245000000])
cbar.set_ticklabels(['0', '50M', '100M', '150M', '200M', '250M'])
cbar.ax.set_ylabel('Qty Users Filing A Claim (millions)', fontsize=12, labelpad=15)

# Add space between the title and the plot
plt.tight_layout()

# Show plot
plt.show()

sample_net_worth = 1000000

penalty_pct/100 * sample_net_worth

# Values
penalty = 725000000
fb_val = 544750000000

# Labels
labels = ['Class Action Lawsuit Penalty', 'Facebook Market Cap']

# Sizes
sizes = [penalty, fb_val]

# Plot
fig, ax = plt.subplots()
ax.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=90)

# Set equal aspect ratio to make the pie chart circular
ax.axis('equal')

# Title
ax.set_title('Facebook Market Cap vs. Class Action Lawsuit Penalty')

plt.show()