Error Distribution

import matplotlib.pyplot as plt
import numpy as np

COLORS = {
    'bars': '#374151',      # Dark gray
    'zero': '#DC2626',      # Professional red
    'std': '#9CA3AF',       # Light gray
    'background': '#FFFFFF',
    'text': '#1E293B',
    'text_muted': '#64748B',
    'grid': '#F1F5F9'
}

np.random.seed(42)
errors = np.random.normal(0, 5, 1000)

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

ax.hist(errors, bins=35, color=COLORS['bars'], edgecolor='white', linewidth=0.5, alpha=0.85)

# Zero line
ax.axvline(0, color=COLORS['zero'], linewidth=2.5, linestyle='-', label='Zero Error')

# ±1 std bands
std = np.std(errors)
ax.axvline(-std, color=COLORS['std'], linewidth=1.5, linestyle='--', alpha=0.8)
ax.axvline(std, color=COLORS['std'], linewidth=1.5, linestyle='--', alpha=0.8, label=f'±1σ ({std:.1f})')

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('Prediction Error', 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=9, labelcolor=COLORS['text_muted'])

plt.tight_layout()
plt.show()