KDE Plot

Wine Cellar Temperature Distribution

KDE of wine storage temperatures with optimal aging zones.

Output
Wine Cellar Temperature Distribution
Python
import matplotlib.pyplot as plt
import numpy as np
from scipy import stats

np.random.seed(210)

temps = np.random.normal(13, 2, 1000)
temps = temps[(temps > 5) & (temps < 22)]

kde = stats.gaussian_kde(temps)
x = np.linspace(5, 22, 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] - 5) / 17
    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(11, 14, alpha=0.2, color='#22d3ee', label='Ideal Aging (11-14C)')
ax.axvspan(7, 10, alpha=0.1, color='#3b82f6', label='White Wine (7-10C)')
ax.axvspan(15, 18, alpha=0.1, color='#fbbf24', label='Red Serving (15-18C)')

ax.set_xlabel('Temperature (C)', fontsize=12, color='#1f2937', fontweight='500')
ax.set_ylabel('Density', fontsize=12, color='#1f2937', fontweight='500')
ax.set_title('Wine Cellar Temperature Distribution', 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', fontsize=9)
ax.grid(True, alpha=0.3, color='#e5e7eb')
ax.set_xlim(5, 22)

plt.tight_layout()
plt.show()
Library

Matplotlib

Category

Statistical

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