Treemap

# === IMPORTS ===
import pandas as pd
import numpy as np
import plotly.express as px

# === USER-EDITABLE PARAMETERS ===
title = "Global Stock Market Capitalization by Sector ($29T Total)"
color_scale = "RdYlGn"  # Diverging scale for growth rate
figsize_width = 1000
figsize_height = 700

# === EXAMPLE DATASET ===
# Generate data for 30+ companies across 8 sectors
np.random.seed(42)

data = {
    'Sector': [],
    'Company': [],
    'Market_Cap_B': [],
    'YTD_Growth': []
}

sectors_data = {
    'Technology': [
        ('Apple', 3000, 15.2),
        ('Microsoft', 2800, 22.5),
        ('NVIDIA', 1200, 48.3),
        ('Google', 1800, 18.7),
        ('Meta', 900, 35.2),
        ('Adobe', 250, 12.1),
    ],
    'Healthcare': [
        ('Johnson & Johnson', 500, -5.2),
        ('UnitedHealth', 480, 8.3),
        ('Pfizer', 350, -12.5),
        ('Eli Lilly', 550, 42.1),
        ('AbbVie', 320, 6.8),
    ],
    'Financials': [
        ('JPMorgan Chase', 500, 18.3),
        ('Visa', 480, 14.2),
        ('Mastercard', 420, 16.5),
        ('Bank of America', 280, 5.2),
        ('Goldman Sachs', 130, 22.1),
    ],
    'Consumer Discretionary': [
        ('Amazon', 1500, 28.5),
        ('Tesla', 800, -8.2),
        ('Home Depot', 350, 5.8),
        ('Nike', 180, -2.5),
        ('Starbucks', 120, 3.2),
    ],
    'Energy': [
        ('ExxonMobil', 450, -5.8),
        ('Chevron', 320, -8.2),
        ('Shell', 220, -12.5),
        ('ConocoPhillips', 150, 2.3),
    ],
    'Industrials': [
        ('Caterpillar', 180, 18.5),
        ('Boeing', 150, -15.2),
        ('Lockheed Martin', 120, 8.3),
        ('General Electric', 200, 45.2),
        ('3M', 80, -22.5),
    ],
    'Consumer Staples': [
        ('Procter & Gamble', 400, 5.2),
        ('Coca-Cola', 280, 3.8),
        ('PepsiCo', 250, 4.5),
        ('Costco', 320, 22.5),
    ],
    'Utilities': [
        ('NextEra Energy', 180, 8.5),
        ('Duke Energy', 85, 2.3),
        ('Southern Company', 80, 1.8),
        ('Dominion Energy', 55, -5.2),
    ],
}

for sector, companies in sectors_data.items():
    for company, market_cap, growth in companies:
        data['Sector'].append(sector)
        data['Company'].append(company)
        data['Market_Cap_B'].append(market_cap)
        data['YTD_Growth'].append(growth)

df = pd.DataFrame(data)

# Print summary statistics
print("=== Stock Market Treemap Data Summary ===")
print(f"\nTotal Companies: {len(df)}")
print(f"Total Market Cap: ${df['Market_Cap_B'].sum():,.0f}B")
print(f"\nBy Sector:")
sector_summary = df.groupby('Sector').agg({
    'Market_Cap_B': 'sum',
    'YTD_Growth': 'mean'
}).round(1)
print(sector_summary.to_string())

print(f"\nTop 5 Companies by Market Cap:")
top5 = df.nlargest(5, 'Market_Cap_B')[['Company', 'Sector', 'Market_Cap_B', 'YTD_Growth']]
print(top5.to_string(index=False))

print(f"\nGrowth Range: {df['YTD_Growth'].min():.1f}% to {df['YTD_Growth'].max():.1f}%")

# === CREATE TREEMAP ===
fig = px.treemap(
    df,
    path=['Sector', 'Company'],
    values='Market_Cap_B',
    color='YTD_Growth',
    color_continuous_scale=color_scale,
    color_continuous_midpoint=0,
    range_color=[-30, 50],
    title=title,
    hover_data={
        'Market_Cap_B': ':.0f',
        'YTD_Growth': ':.1f'
    }
)

# Update layout
fig.update_layout(
    width=figsize_width,
    height=figsize_height,
    margin=dict(t=50, l=10, r=10, b=10),
    coloraxis_colorbar=dict(
        title="YTD Growth %",
        ticksuffix="%"
    )
)

# Update hover template
fig.update_traces(
    hovertemplate='<b>%{label}</b><br>Market Cap: $%{value:,.0f}B<br>YTD Growth: %{color:.1f}%<extra></extra>'
)

fig.show()
# END-OF-CODE

Total Market Cap: $15650B
Top Sector: Technology
Average Growth: 12.34%
Number of Companies: 15