Coffee Bean Quality Score KDE

import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import gaussian_kde

np.random.seed(1212)
BG_COLOR = '#ffffff'
TEXT_COLOR = '#1f2937'
GRID_COLOR = '#e5e7eb'

# Cupping scores (0-100)
ethiopia = np.random.normal(86, 4, 300)
colombia = np.random.normal(84, 5, 300)
brazil = np.random.normal(82, 5, 300)

fig, ax = plt.subplots(figsize=(10, 6), facecolor=BG_COLOR)
ax.set_facecolor(BG_COLOR)

x_range = np.linspace(65, 100, 500)

for data, color, label in [(ethiopia, '#9C2007', 'Ethiopia'), 
                            (colombia, '#F5B027', 'Colombia'),
                            (brazil, '#6CF527', 'Brazil')]:
    kde = gaussian_kde(data)
    density = kde(x_range)
    ax.plot(x_range, density, color=color, linewidth=2.5, label=label)
    ax.fill_between(x_range, density, alpha=0.25, color=color)

ax.axvline(80, color='#4927F5', linestyle='--', alpha=0.7, linewidth=2)
ax.text(80.5, ax.get_ylim()[1]*0.85, 'Specialty', color='#4927F5', fontsize=10)

ax.set_xlabel('Cupping Score', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_ylabel('Density', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_title('Coffee Quality Score by Origin', fontsize=14, color=TEXT_COLOR, fontweight='bold', pad=15)

ax.tick_params(colors=TEXT_COLOR, labelsize=10)
for spine in ax.spines.values():
    spine.set_color(GRID_COLOR)
ax.yaxis.grid(True, color=GRID_COLOR, linewidth=0.5, alpha=0.7)
ax.legend(facecolor=BG_COLOR, edgecolor=GRID_COLOR, labelcolor=TEXT_COLOR, fontsize=10)

plt.tight_layout()
plt.show()