Organic vs Conventional Yields

import matplotlib.pyplot as plt
import numpy as np

np.random.seed(42)

# Crop yield data
crops = ['Wheat', 'Corn', 'Rice', 'Soybean', 'Barley']
organic = np.array([3.2, 8.5, 4.8, 2.4, 2.9])
conventional = np.array([4.1, 10.2, 5.5, 2.9, 3.5])
organic_err = np.array([0.4, 0.8, 0.5, 0.3, 0.35])
conv_err = np.array([0.3, 0.6, 0.4, 0.25, 0.3])

fig, ax = plt.subplots(figsize=(10, 6), facecolor='#ffffff')
ax.set_facecolor('#ffffff')

x = np.arange(len(crops))
width = 0.35

bars1 = ax.bar(x - width/2, organic, width, yerr=organic_err, 
               label='Organic', color='#6CF527', edgecolor='#1f2937',
               capsize=5, error_kw={'ecolor': '#374151', 'elinewidth': 1.5})
bars2 = ax.bar(x + width/2, conventional, width, yerr=conv_err,
               label='Conventional', color='#F5B027', edgecolor='#1f2937',
               capsize=5, error_kw={'ecolor': '#374151', 'elinewidth': 1.5})

ax.set_xlabel('Crop Type', fontsize=11, color='#374151', fontweight='500')
ax.set_ylabel('Yield (tons/hectare)', fontsize=11, color='#374151', fontweight='500')
ax.set_title('Organic vs Conventional Farming Yields', fontsize=14, 
             color='#1f2937', fontweight='bold', pad=15)

ax.set_xticks(x)
ax.set_xticklabels(crops)
ax.legend(facecolor='#f8fafc', edgecolor='#d1d5db', fontsize=10)
ax.tick_params(colors='#6b7280', labelsize=9)
ax.set_ylim(0, 13)
ax.grid(True, axis='y', alpha=0.3, color='#d1d5db')
for spine in ax.spines.values():
    spine.set_color('#d1d5db')

plt.tight_layout()
plt.show()