Waterfall Chart
Employee Compensation Breakdown
Total compensation waterfall from base salary through benefits and taxes.
Output
Python
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Patch
categories = ['Base\nSalary', 'Annual\nBonus', 'Stock\nGrants', 'Health\nInsurance',
'401k\nMatch', 'Payroll\nTaxes', 'Other\nBenefits', 'Total\nComp Cost']
values = [0, 25, 40, 18, 8, 15, 6, 0]
initial = 120
running_total = initial
bottoms, heights, colors = [], [], []
palette = ['#6CF527', '#4927F5', '#27D3F5', '#F5B027', '#F5276C', '#27F5B0']
for i, (cat, val) in enumerate(zip(categories, values)):
if 'Base' in cat:
bottoms.append(0)
heights.append(initial)
colors.append('#27D3F5')
elif 'Total' in cat:
bottoms.append(0)
heights.append(running_total)
colors.append('#F5276C')
else:
bottoms.append(running_total)
heights.append(val)
colors.append(palette[(i-1) % len(palette)])
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 'Base' in categories[i] or 'Total' in categories[i]:
label = f"${height}K"
ax.text(bar.get_x() + bar.get_width()/2, y_pos, label, ha='center', va='center',
fontsize=11, fontweight='bold', color='white')
else:
label = f"+${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 = 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)
ax.set_xlim(-0.6, len(categories) - 0.4)
ax.set_ylim(0, running_total * 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('Total Employee Compensation Cost', 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')
burden_rate = ((running_total - initial) / initial) * 100
ax.annotate(f'Benefits Burden Rate: {burden_rate:.0f}%', xy=(0.98, 0.95), xycoords='axes fraction',
fontsize=11, color='#F5B027', ha='right', fontweight='bold',
bbox=dict(boxstyle='round,pad=0.4', facecolor='#1e293b', edgecolor='#F5B027', alpha=0.9))
legend_elements = [Patch(facecolor='#27D3F5', label='Base Salary'), Patch(facecolor='#6CF527', label='Cash Comp'),
Patch(facecolor='#F5B027', label='Benefits'), Patch(facecolor='#F5276C', label='Total Cost')]
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()
Library
Matplotlib
Category
Financial
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