Waterfall Chart
Cost Reduction Initiative Impact
Dark-themed waterfall chart showing the impact of various cost reduction initiatives on total operating costs.
Output
Python
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Patch
# Cost reduction initiatives (in millions)
categories = ['Baseline\nCosts', 'Automation', 'Outsourcing', 'Renegotiated\nContracts',
'Workforce\nOptimization', 'Energy\nEfficiency', 'New\nInvestments', 'Target\nCosts']
values = [0, -25, -18, -12, -35, -8, 15, 0]
# Calculate running total
initial = 420
running_total = initial
bottoms = []
heights = []
colors = []
for i, (cat, val) in enumerate(zip(categories, values)):
if 'Baseline' in cat:
bottoms.append(0)
heights.append(initial)
colors.append('#F5276C')
elif 'Target' in cat:
bottoms.append(0)
heights.append(running_total)
colors.append('#6CF527')
elif val < 0:
bottoms.append(running_total + val)
heights.append(abs(val))
colors.append('#27F5B0')
running_total += val
else:
bottoms.append(running_total)
heights.append(val)
colors.append('#F5B027')
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 'Baseline' in categories[i] or 'Target' in categories[i]:
label = f"${height}M"
ax.text(bar.get_x() + bar.get_width()/2, y_pos, label,
ha='center', va='center', fontsize=11, fontweight='bold', color='white')
else:
label = f"-${abs(val)}M" if val < 0 else f"+${val}M"
ax.text(bar.get_x() + bar.get_width()/2, y_pos, label,
ha='center', va='center', fontsize=10, fontweight='bold', color='white' if height > 10 else '#0a0a0f')
# Connect bars
for i in range(len(x) - 1):
if i == 0:
y = initial
else:
y = bottoms[i]
ax.plot([x[i] + 0.35, x[i+1] - 0.35], [y, y],
color='#475569', linestyle='--', linewidth=1.5, alpha=0.7)
# Styling
ax.set_xlim(-0.6, len(categories) - 0.4)
ax.set_ylim(0, initial * 1.1)
ax.set_xticks(x)
ax.set_xticklabels(categories, fontsize=9, color='#e2e8f0')
ax.set_ylabel('Annual Costs ($ Millions)', fontsize=12, color='#e2e8f0', fontweight='500')
ax.set_title('Cost Reduction Initiative Impact 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')
# Savings annotation
savings = initial - running_total
pct = (savings / initial) * 100
ax.annotate(f'Total Savings: ${savings}M ({pct:.1f}%)', xy=(0.98, 0.95), xycoords='axes fraction',
fontsize=11, color='#6CF527', ha='right', fontweight='bold',
bbox=dict(boxstyle='round,pad=0.4', facecolor='#1e293b', edgecolor='#6CF527', alpha=0.9))
# Legend outside plot
legend_elements = [
Patch(facecolor='#F5276C', label='Baseline Costs'),
Patch(facecolor='#27F5B0', label='Cost Savings'),
Patch(facecolor='#F5B027', label='New Investments'),
Patch(facecolor='#6CF527', label='Target Costs')
]
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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