Ridgeline Plot
Smart Home Energy Usage
IoT power consumption with eco-green neon theme
Output
Python
import matplotlib.pyplot as plt
import numpy as np
from scipy import stats
np.random.seed(1111)
devices = ['HVAC', 'Lighting', 'Appliances', 'EV Charger', 'Entertainment', 'Security']
colors = ['#F54927', '#F5D327', '#6CF527', '#27D3F5', '#F5276C', '#4927F5']
data = {
'HVAC': np.random.gamma(8, 0.5, 500),
'Lighting': np.random.gamma(2, 0.3, 500),
'Appliances': np.random.gamma(4, 0.4, 500),
'EV Charger': np.random.gamma(6, 0.8, 500),
'Entertainment': np.random.gamma(2.5, 0.35, 500),
'Security': np.random.gamma(1, 0.2, 500)
}
fig, ax = plt.subplots(figsize=(12, 8), facecolor='#ffffff')
ax.set_facecolor('#ffffff')
overlap = 1.6
x_range = np.linspace(0, 10, 300)
for i, (device, kwh) in enumerate(data.items()):
kde = stats.gaussian_kde(kwh, bw_method=0.3)
y = kde(x_range) * 3.5
baseline = i * overlap
ax.fill_between(x_range, baseline, y + baseline, alpha=0.7, color=colors[i])
ax.plot(x_range, y + baseline, color=colors[i], linewidth=2.5)
ax.text(-0.2, baseline + 0.12, device, fontsize=10, color='#1f2937',
ha='right', va='bottom', fontweight='600')
ax.set_xlim(-2.5, 10)
ax.set_ylim(-0.3, len(devices) * overlap + 1.8)
ax.set_xlabel('Daily Usage (kWh)', fontsize=12, color='#374151', fontweight='500')
ax.set_title('Smart Home Energy Usage', fontsize=16, color='#1f2937', fontweight='bold', pad=20)
ax.tick_params(axis='x', colors='#374151', labelsize=10)
ax.tick_params(axis='y', left=False, labelleft=False)
ax.spines['bottom'].set_color('#e5e7eb')
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(False)
plt.tight_layout()
plt.show()
Library
Matplotlib
Category
Statistical
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