Sprint Performance Comparison

import matplotlib.pyplot as plt
import numpy as np

np.random.seed(42)

# Athletic data - sprint times
athletes = ['Thompson', 'Fraser-Pryce', 'Jackson', 'Richardson', 'Ta Lou']
times_100m = np.array([10.54, 10.62, 10.65, 10.71, 10.78])
times_200m = np.array([21.45, 21.79, 21.52, 21.85, 22.15])
err_100m = np.array([0.05, 0.06, 0.04, 0.07, 0.05])
err_200m = np.array([0.12, 0.14, 0.10, 0.15, 0.11])

fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 5), facecolor='#0a0a0f')

for ax in [ax1, ax2]:
    ax.set_facecolor('#0a0a0f')

# 100m
y_pos = np.arange(len(athletes))
ax1.barh(y_pos, times_100m, xerr=err_100m, height=0.6, color='#F5B027',
         edgecolor='white', capsize=4,
         error_kw={'ecolor': 'white', 'elinewidth': 1.5, 'capthick': 1.5})
ax1.set_yticks(y_pos)
ax1.set_yticklabels(athletes)
ax1.set_xlabel('Time (seconds)', fontsize=11, color='white', fontweight='500')
ax1.set_title('100m Sprint Times', fontsize=13, color='white', fontweight='bold', pad=10)
ax1.set_xlim(10.3, 11.0)
ax1.invert_xaxis()
ax1.tick_params(colors='#94a3b8', labelsize=9)
ax1.grid(True, axis='x', alpha=0.2, color='#4a4a6a')
for spine in ax1.spines.values():
    spine.set_color('#333333')

# 200m  
ax2.barh(y_pos, times_200m, xerr=err_200m, height=0.6, color='#27D3F5',
         edgecolor='white', capsize=4,
         error_kw={'ecolor': 'white', 'elinewidth': 1.5, 'capthick': 1.5})
ax2.set_yticks(y_pos)
ax2.set_yticklabels([])
ax2.set_xlabel('Time (seconds)', fontsize=11, color='white', fontweight='500')
ax2.set_title('200m Sprint Times', fontsize=13, color='white', fontweight='bold', pad=10)
ax2.set_xlim(21.0, 22.5)
ax2.tick_params(colors='#94a3b8', labelsize=9)
ax2.grid(True, axis='x', alpha=0.2, color='#4a4a6a')
for spine in ax2.spines.values():
    spine.set_color('#333333')

plt.suptitle('Elite Sprinter Performance Comparison', fontsize=14, 
             color='white', fontweight='bold', y=1.02)
plt.tight_layout()
plt.show()