Workout Duration by Type

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

np.random.seed(42)
workouts = ['Yoga', 'Strength', 'Cardio', 'HIIT', 'CrossFit', 'Pilates', 'Cycling']
duration_means = [55, 65, 45, 30, 50, 50, 60]
duration_stds = [15, 18, 15, 8, 12, 12, 20]

fig, ax = plt.subplots(figsize=(12, 9), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

colors = ['#27F5B0', '#F5276C', '#F54927', '#F5B027', '#6CF527', '#27D3F5', '#4927F5']

x = np.linspace(0, 120, 200)
overlap = 2.0

for i, (workout, mean, std, color) in enumerate(zip(workouts, duration_means, duration_stds, colors)):
    data = np.random.normal(mean, std, 1000)
    data = np.clip(data, 10, None)
    kde = stats.gaussian_kde(data)
    y = kde(x) * 10
    y_offset = i * overlap
    
    ax.fill_between(x, y_offset, y + y_offset, alpha=0.85, color=color, edgecolor='white', linewidth=0.8)
    ax.text(-5, y_offset + 0.3, workout, fontsize=10, color='white', va='center', ha='right', fontweight='500')

ax.set_xlim(-25, 120)
ax.set_ylim(-0.5, len(workouts) * overlap + 2)
ax.set_xlabel('Workout Duration (minutes)', color='white', fontsize=11, fontweight='500')
ax.set_title('Workout Duration Distribution by Type', color='white', fontsize=14, fontweight='bold', pad=20)
ax.tick_params(colors='#888888', labelsize=9)
ax.set_yticks([])
for spine in ax.spines.values():
    spine.set_visible(False)
ax.spines['bottom'].set_visible(True)
ax.spines['bottom'].set_color('#333333')

plt.tight_layout()
plt.show()