Air Quality PM2.5 Distribution

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

np.random.seed(113)

pm25 = np.random.lognormal(2.5, 0.7, 1000)
pm25 = pm25[pm25 < 150]

kde = stats.gaussian_kde(pm25)
x = np.linspace(0, 150, 500)
y = kde(x)

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

for i in range(len(x)-1):
    if x[i] < 12:
        color = '#6CF527'
    elif x[i] < 35:
        color = '#D3F527'
    elif x[i] < 55:
        color = '#F5B027'
    elif x[i] < 150:
        color = '#F5276C'
    else:
        color = '#4927F5'
    ax.fill_between(x[i:i+2], y[i:i+2], alpha=0.5, color=color)

ax.plot(x, y, color='#6CF527', linewidth=3)

levels = [(12, 'Good'), (35, 'Moderate'), (55, 'Unhealthy')]
for val, label in levels:
    ax.axvline(val, color='#9ca3af', linestyle='--', linewidth=1.5)
    ax.text(val+2, max(y)*0.85, label, color='#6b7280', fontsize=9, fontweight='bold')

ax.set_xlabel('PM2.5 Concentration (ug/m3)', fontsize=12, color='#1f2937', fontweight='500')
ax.set_ylabel('Density', fontsize=12, color='#1f2937', fontweight='500')
ax.set_title('Air Quality PM2.5 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.grid(True, alpha=0.3, color='#e5e7eb')
ax.set_xlim(0, 150)

plt.tight_layout()
plt.show()