Real Estate Investment Returns

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Patch

categories = ['Gross\nRental Income', 'Vacancy\nLoss', 'Property\nMgmt', 'Maintenance', 
              'Property\nTaxes', 'Insurance', 'Mortgage\nPayment', 'Net\nCash Flow']
values = [0, -12, -18, -15, -24, -8, -85, 0]

initial = 240
running_total = initial
bottoms, heights, colors = [], [], []

for i, (cat, val) in enumerate(zip(categories, values)):
    if 'Gross' in cat:
        bottoms.append(0)
        heights.append(initial)
        colors.append('#27D3F5')
    elif 'Net' in cat:
        bottoms.append(0)
        heights.append(running_total)
        colors.append('#6CF527' if running_total > 0 else '#F5276C')
    else:
        bottoms.append(running_total + val)
        heights.append(abs(val))
        colors.append('#F5276C')
        running_total += val

fig, ax = plt.subplots(figsize=(14, 8), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

x = np.arange(len(categories))
bars = ax.bar(x, heights, bottom=bottoms, color=colors, width=0.65, edgecolor='#1e293b', linewidth=1)

for i, (bar, val, bot, height) in enumerate(zip(bars, values, bottoms, heights)):
    y_pos = bot + height / 2
    if 'Gross' in categories[i] or 'Net' in categories[i]:
        label = f"${height}K"
        ax.text(bar.get_x() + bar.get_width()/2, y_pos, label, ha='center', va='center', 
                fontsize=11, fontweight='bold', color='#0a0a0f' if height > 100 else 'white')
    else:
        label = f"${abs(val)}K"
        ax.text(bar.get_x() + bar.get_width()/2, y_pos, label, ha='center', va='center', 
                fontsize=10, fontweight='bold', color='white')

for i in range(len(x) - 1):
    y = initial if i == 0 else bottoms[i]
    ax.plot([x[i] + 0.35, x[i+1] - 0.35], [y, y], color='#475569', linestyle='--', linewidth=1.5, alpha=0.7)

ax.set_xlim(-0.6, len(categories) - 0.4)
ax.set_ylim(0, initial * 1.1)
ax.set_xticks(x)
ax.set_xticklabels(categories, fontsize=9, color='#e2e8f0')
ax.set_ylabel('Annual Amount ($ Thousands)', fontsize=12, color='#e2e8f0', fontweight='500')
ax.set_title('Rental Property Cash Flow Analysis', fontsize=16, color='white', fontweight='bold', pad=20)
ax.tick_params(axis='y', colors='#e2e8f0', labelsize=10)
ax.yaxis.grid(True, linestyle='--', alpha=0.3, color='#334155')
ax.set_axisbelow(True)
for spine in ax.spines.values():
    spine.set_color('#334155')

# Cap rate calculation (assuming $2M property value)
noi = running_total + 85  # Add back mortgage for NOI
cap_rate = (noi / 2000) * 100
cash_on_cash = (running_total / 400) * 100  # Assuming $400K down payment
ax.annotate(f'Cap Rate: {cap_rate:.1f}% | Cash-on-Cash: {cash_on_cash:.1f}%', xy=(0.98, 0.95), xycoords='axes fraction',
            fontsize=10, color='#6CF527', ha='right', fontweight='bold',
            bbox=dict(boxstyle='round,pad=0.4', facecolor='#1e293b', edgecolor='#6CF527', alpha=0.9))

legend_elements = [Patch(facecolor='#27D3F5', label='Gross Income'), Patch(facecolor='#F5276C', label='Expenses'),
                   Patch(facecolor='#6CF527', label='Net Cash Flow')]
ax.legend(handles=legend_elements, loc='upper left', bbox_to_anchor=(0, -0.1), ncol=3, fontsize=9,
          facecolor='#1e293b', edgecolor='#334155', labelcolor='white')

plt.tight_layout()
plt.subplots_adjust(bottom=0.15)
plt.show()