KDE Plot
Beverage Temperature Preference
KDE showing preferred drinking temperatures for hot beverages.
Output
Python
import matplotlib.pyplot as plt
import numpy as np
from scipy import stats
np.random.seed(207)
coffee = np.random.normal(65, 8, 500)
tea = np.random.normal(72, 10, 400)
temps = np.concatenate([coffee, tea])
temps = temps[(temps > 40) & (temps < 95)]
kde = stats.gaussian_kde(temps)
x = np.linspace(40, 95, 500)
y = kde(x)
colors = ['#1e3a8a', '#3b82f6', '#22d3ee', '#fbbf24', '#f97316', '#dc2626']
fig, ax = plt.subplots(figsize=(12, 6), facecolor='#ffffff')
ax.set_facecolor('#ffffff')
for i in range(len(x)-1):
norm_val = (x[i] - 40) / 55
color_idx = int(norm_val * (len(colors) - 1))
color_idx = max(0, min(color_idx, len(colors)-1))
ax.fill_between(x[i:i+2], y[i:i+2], alpha=0.6, color=colors[color_idx])
ax.plot(x, y, color='#374151', linewidth=2.5)
ax.axvspan(60, 70, alpha=0.15, color='#22d3ee', label='Optimal Drinking (60-70C)')
ax.axvline(82, color='#dc2626', linestyle='--', linewidth=2, label='Burn Risk (>82C)')
ax.set_xlabel('Temperature (C)', fontsize=12, color='#1f2937', fontweight='500')
ax.set_ylabel('Density', fontsize=12, color='#1f2937', fontweight='500')
ax.set_title('Hot Beverage Temperature Preference', fontsize=16, color='#1f2937', fontweight='bold', pad=15)
ax.tick_params(colors='#374151', labelsize=10)
for spine in ax.spines.values():
spine.set_color('#d1d5db')
ax.legend(loc='upper right', facecolor='#f9fafb', edgecolor='#d1d5db', labelcolor='#374151')
ax.grid(True, alpha=0.3, color='#e5e7eb')
ax.set_xlim(40, 95)
plt.tight_layout()
plt.show()
Library
Matplotlib
Category
Statistical
☕