Vehicle Type Classification Light

import matplotlib.pyplot as plt
import numpy as np
from scipy.cluster.hierarchy import dendrogram, linkage, set_link_color_palette

np.random.seed(369)

vehicles = ['Sedan', 'SUV', 'Truck', 'Coupe', 'Hatchback', 'Minivan',
            'Sports Car', 'Convertible', 'Wagon', 'Crossover', 'EV Sedan', 'EV SUV']

specs = np.random.rand(len(vehicles), 6) * 100
Z = linkage(specs, method='ward')

fig, ax = plt.subplots(figsize=(13, 7), facecolor='#ffffff')
ax.set_facecolor('#ffffff')

set_link_color_palette(['#F5276C', '#27D3F5', '#6CF527', '#F5D327', '#5314E6'])

dn = dendrogram(Z, labels=vehicles, leaf_rotation=40, leaf_font_size=11,
                color_threshold=0.65*max(Z[:,2]), above_threshold_color='#9ca3af', ax=ax)

ax.set_title('Vehicle Type Classification Hierarchy', fontsize=15, 
             color='#1f2937', fontweight='bold', pad=18)
ax.set_xlabel('Vehicle Type', fontsize=11, color='#374151')
ax.set_ylabel('Specification Distance', fontsize=11, color='#374151')

ax.tick_params(axis='both', colors='#374151', labelsize=10)
for spine in ['top', 'right']:
    ax.spines[spine].set_visible(False)
for spine in ['left', 'bottom']:
    ax.spines[spine].set_color('#e5e7eb')
ax.yaxis.grid(True, color='#f9fafb', linewidth=0.8)

plt.tight_layout()
plt.show()