M&A Synergy Analysis

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

# M&A synergy data (in millions)
categories = ['Pre-Deal', 'Revenue\nSynergies', 'Cost\nSavings', 'Procurement\nEfficiency', 
              'Workforce\nOptimization', 'Tech\nIntegration', 'Integration\nCosts', 'Post-Deal']
values = [0, 45, 62, 28, 35, 18, -48, 0]

# Calculate running total
initial = 320
running_total = initial
bottoms = []
heights = []
colors = []

for i, (cat, val) in enumerate(zip(categories, values)):
    if cat == 'Pre-Deal':
        bottoms.append(0)
        heights.append(initial)
        colors.append('#27D3F5')
    elif cat == 'Post-Deal':
        bottoms.append(0)
        heights.append(running_total)
        colors.append('#6CF527')
    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='#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)

# 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 ['Pre-Deal', 'Post-Deal']:
        label = f"${height}M"
        ax.text(bar.get_x() + bar.get_width()/2, y_pos, label, 
                ha='center', va='center', fontsize=11, fontweight='bold', color='#0a0a0f')
    else:
        label = f"+${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='white')

# 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='#475569', 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='#e2e8f0')
ax.set_ylabel('Value ($ Millions)', fontsize=12, color='#e2e8f0', fontweight='500')
ax.set_title('M&A Integration Synergy Realization', 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')

# Legend outside plot
legend_elements = [
    Patch(facecolor='#27D3F5', label='Pre-Deal Value'),
    Patch(facecolor='#27F5B0', label='Synergy Gains'),
    Patch(facecolor='#F5276C', label='Integration Costs'),
    Patch(facecolor='#6CF527', label='Post-Deal Value')
]
ax.legend(handles=legend_elements, loc='upper left', bbox_to_anchor=(0, -0.1), 
          ncol=4, fontsize=9, facecolor='#1e293b', edgecolor='#334155', labelcolor='white')

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