Free Cash Flow Bridge Analysis

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

# FCF bridge (in millions)
categories = ['Net\nIncome', 'D&A', 'Stock-Based\nComp', 'Working\nCapital', 
              'Deferred\nTaxes', 'CapEx', 'Acquisitions', 'Free\nCash Flow']
values = [0, 85, 42, -38, 15, -120, -45, 0]

# Calculate running total
initial = 280
running_total = initial
bottoms = []
heights = []
colors = []

for i, (cat, val) in enumerate(zip(categories, values)):
    if cat == 'Net\nIncome':
        bottoms.append(0)
        heights.append(initial)
        colors.append('#276CF5')
    elif cat == 'Free\nCash Flow':
        bottoms.append(0)
        heights.append(running_total)
        colors.append('#6CF527' if running_total > 0 else '#F5276C')
    elif val > 0:
        bottoms.append(running_total)
        heights.append(val)
        colors.append('#27F5B0')
        running_total += val
    else:
        bottoms.append(running_total + val)
        heights.append(abs(val))
        colors.append('#F5276C')
        running_total += val

# Create figure
fig, ax = plt.subplots(figsize=(14, 8), facecolor='#ffffff')
ax.set_facecolor('#ffffff')

x = np.arange(len(categories))
bars = ax.bar(x, heights, bottom=bottoms, color=colors, width=0.65, edgecolor='#e5e7eb', linewidth=1)

# Add value labels
for i, (bar, val, bot, height) in enumerate(zip(bars, values, bottoms, heights)):
    y_pos = bot + height / 2
    if categories[i] in ['Net\nIncome', 'Free\nCash Flow']:
        label = f"${height}M"
        ax.text(bar.get_x() + bar.get_width()/2, y_pos, label, 
                ha='center', va='center', fontsize=11, fontweight='bold', color='#374151')
    else:
        label = f"+${val}M" if val > 0 else f"-${abs(val)}M"
        ax.text(bar.get_x() + bar.get_width()/2, y_pos, label, 
                ha='center', va='center', fontsize=10, fontweight='bold', color='#374151')

# Connect bars
for i in range(len(x) - 1):
    if i == 0:
        y = initial
    else:
        y = bottoms[i] + heights[i]
    ax.plot([x[i] + 0.35, x[i+1] - 0.35], [y, y], 
            color='#9ca3af', linestyle='--', linewidth=1.5, alpha=0.7)

# Styling
ax.set_xlim(-0.6, len(categories) - 0.4)
ax.set_ylim(0, max(bottoms[i] + heights[i] for i in range(len(heights))) * 1.1)
ax.set_xticks(x)
ax.set_xticklabels(categories, fontsize=10, color='#374151')
ax.set_ylabel('Value ($ Millions)', fontsize=12, color='#374151', fontweight='500')
ax.set_title('Free Cash Flow Bridge: Net Income to FCF', fontsize=16, color='#374151', fontweight='bold', pad=20)

ax.tick_params(axis='y', colors='#e2e8f0', labelsize=10)
ax.yaxis.grid(True, linestyle='--', alpha=0.3, color='#e5e7eb')
ax.set_axisbelow(True)

for spine in ax.spines.values():
    spine.set_color('#334155')

# Legend outside plot
legend_elements = [
    Patch(facecolor='#276CF5', label='Net Income'),
    Patch(facecolor='#27F5B0', label='Non-Cash Add-backs'),
    Patch(facecolor='#F5276C', label='Cash Uses'),
    Patch(facecolor='#6CF527', label='Free Cash Flow')
]
ax.legend(handles=legend_elements, loc='upper left', bbox_to_anchor=(0, -0.1), 
          ncol=4, fontsize=9, facecolor='white', edgecolor='#e5e7eb', labelcolor='#374151')

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