Dual Stairs Comparison

import matplotlib.pyplot as plt
import numpy as np

COLORS = {
    'before': '#6366F1',
    'after': '#10B981',
    'background': '#FFFFFF',
    'text': '#1E293B',
    'text_muted': '#64748B',
    'grid': '#F1F5F9'
}

np.random.seed(42)
before = np.random.normal(40, 12, 500)
after = np.random.normal(58, 10, 500)
bins = np.linspace(0, 100, 25)
counts_before, _ = np.histogram(before, bins=bins)
counts_after, _ = np.histogram(after, bins=bins)

fig, ax = plt.subplots(figsize=(10, 6), dpi=100)
ax.set_facecolor(COLORS['background'])
fig.patch.set_facecolor(COLORS['background'])

# Before - clean outline only
ax.stairs(counts_before, bins, linewidth=2.5, color=COLORS['before'], fill=True, alpha=0.15, label='Before')
ax.stairs(counts_before, bins, linewidth=2.5, color=COLORS['before'])

# After - clean outline only
ax.stairs(counts_after, bins, linewidth=2.5, color=COLORS['after'], fill=True, alpha=0.15, label='After')
ax.stairs(counts_after, bins, linewidth=2.5, color=COLORS['after'])

# Mean markers
mean_before = np.mean(before)
mean_after = np.mean(after)
ax.axvline(mean_before, color=COLORS['before'], linewidth=2, linestyle='--', alpha=0.7)
ax.axvline(mean_after, color=COLORS['after'], linewidth=2, linestyle='--', alpha=0.7)

# Labels at top
y_top = max(max(counts_before), max(counts_after)) + 3
ax.scatter([mean_before], [y_top], marker='v', s=60, c=COLORS['before'], zorder=5)
ax.scatter([mean_after], [y_top], marker='v', s=60, c=COLORS['after'], zorder=5)

ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_color(COLORS['grid'])
ax.spines['bottom'].set_color(COLORS['grid'])
ax.yaxis.grid(True, color=COLORS['grid'], linewidth=1, zorder=0)
ax.set_axisbelow(True)
ax.tick_params(axis='both', colors=COLORS['text_muted'], labelsize=9, length=0, pad=8)
ax.set_xlabel('Score', fontsize=10, color=COLORS['text'], labelpad=10)
ax.set_ylabel('Count', fontsize=10, color=COLORS['text'], labelpad=10)
ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.12), ncol=2, frameon=False, fontsize=10, labelcolor=COLORS['text_muted'])

plt.tight_layout()
plt.show()