Weekly Grocery Spending Distribution

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

np.random.seed(116)

spending = np.random.gamma(8, 15, 1000)
spending = spending[spending < 300]

kde = stats.gaussian_kde(spending)
x = np.linspace(0, 300, 500)
y = kde(x)

fig, ax = plt.subplots(figsize=(12, 6), facecolor='#ffffff')
ax.set_facecolor('#ffffff')

ax.fill_between(x, y, alpha=0.4, color='#27F5B0')
ax.plot(x, y, color='#27F5B0', linewidth=3)

mean_spend = np.mean(spending)
p25 = np.percentile(spending, 25)
p75 = np.percentile(spending, 75)

ax.axvspan(p25, p75, alpha=0.15, color='#27D3F5', label='Middle 50%')
ax.axvline(mean_spend, color='#374151', linestyle='--', linewidth=2, label='Mean: $' + str(int(mean_spend)))

ax.set_xlabel('Weekly Spending ($)', fontsize=12, color='#1f2937', fontweight='500')
ax.set_ylabel('Density', fontsize=12, color='#1f2937', fontweight='500')
ax.set_title('Weekly Grocery Spending 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')
ax.grid(True, alpha=0.3, color='#e5e7eb')
ax.set_xlim(0, 300)

plt.tight_layout()
plt.show()