Agricultural Soil Nutrient Comparison

import matplotlib.pyplot as plt
import numpy as np

np.random.seed(42)

# Soil nutrient data
nutrients = ['Nitrogen\n(N)', 'Phosphorus\n(P)', 'Potassium\n(K)', 'Calcium\n(Ca)', 'Magnesium\n(Mg)', 'Sulfur\n(S)']
field_a = np.array([45, 28, 180, 1200, 150, 22])
field_b = np.array([52, 22, 165, 980, 185, 18])
field_c = np.array([38, 35, 195, 1450, 120, 28])
err_a = np.array([5, 4, 15, 80, 12, 3])
err_b = np.array([6, 3, 12, 65, 15, 2])
err_c = np.array([4, 5, 18, 95, 10, 4])

# Normalize to percentage of optimal
optimal = np.array([50, 30, 200, 1200, 160, 25])
field_a_pct = field_a / optimal * 100
field_b_pct = field_b / optimal * 100
field_c_pct = field_c / optimal * 100
err_a_pct = err_a / optimal * 100
err_b_pct = err_b / optimal * 100
err_c_pct = err_c / optimal * 100

fig, ax = plt.subplots(figsize=(10, 6), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

x = np.arange(len(nutrients))
width = 0.25

ax.bar(x - width, field_a_pct, width, yerr=err_a_pct, label='Field A',
       color='#27D3F5', edgecolor='white', capsize=3,
       error_kw={'ecolor': 'white', 'elinewidth': 1.2})
ax.bar(x, field_b_pct, width, yerr=err_b_pct, label='Field B',
       color='#F5B027', edgecolor='white', capsize=3,
       error_kw={'ecolor': 'white', 'elinewidth': 1.2})
ax.bar(x + width, field_c_pct, width, yerr=err_c_pct, label='Field C',
       color='#6CF527', edgecolor='white', capsize=3,
       error_kw={'ecolor': 'white', 'elinewidth': 1.2})

ax.axhline(y=100, color='#F5276C', linestyle='--', linewidth=2, 
           label='Optimal Level', alpha=0.8)

ax.set_xlabel('Nutrient', fontsize=11, color='white', fontweight='500')
ax.set_ylabel('% of Optimal Level', fontsize=11, color='white', fontweight='500')
ax.set_title('Agricultural Soil Nutrient Comparison', fontsize=14, 
             color='white', fontweight='bold', pad=15)

ax.set_xticks(x)
ax.set_xticklabels(nutrients)
ax.legend(facecolor='#1a1a2e', edgecolor='#333', labelcolor='white', 
          fontsize=9, loc='upper right')
ax.tick_params(colors='#94a3b8', labelsize=9)
ax.set_ylim(0, 140)
ax.grid(True, axis='y', alpha=0.2, color='#4a4a6a')
for spine in ax.spines.values():
    spine.set_color('#333333')

plt.tight_layout()
plt.show()