Product Feature Comparison

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
from matplotlib.colors import LinearSegmentedColormap

np.random.seed(555)

features = ['Performance', 'Battery', 'Display', 'Camera', 'Storage',
            'Build Quality', 'Software', 'Price Value', 'Support', 'Ecosystem']
products = ['iPhone 15', 'Galaxy S24', 'Pixel 8', 'OnePlus 12', 'Xiaomi 14',
            'Sony Xperia', 'Asus ROG', 'Nothing Phone']

data = np.random.rand(10, 8) * 3 + 5
data[9, 0] += 2
data[0, 6] += 2
data[7, 4:6] += 1.5

df = pd.DataFrame(data, index=features, columns=products)

tiers = ['Premium']*3 + ['Mid-range']*3 + ['Gaming'] + ['Budget']
tier_palette = {'Premium': '#6366f1', 'Mid-range': '#22c55e', 'Gaming': '#ef4444', 'Budget': '#f59e0b'}
col_colors = pd.Series(tiers, index=products).map(tier_palette)

light_cmap = LinearSegmentedColormap.from_list('rating', ['#fee2e2', '#fef9c3', '#d1fae5', '#059669'])

g = sns.clustermap(df, cmap=light_cmap, vmin=5, vmax=10, col_colors=col_colors,
                   method='average', metric='euclidean',
                   linewidths=0.5, linecolor='#e5e7eb',
                   figsize=(9, 8), dendrogram_ratio=(0.12, 0.12),
                   annot=True, fmt='.1f', annot_kws={'size': 8, 'color': '#374151'},
                   cbar_pos=(0.01, 0.08, 0.008, 0.12))

g.fig.patch.set_facecolor('#ffffff')
g.ax_heatmap.set_facecolor('#ffffff')
g.ax_heatmap.tick_params(colors='#1f2937', labelsize=8)
g.ax_row_dendrogram.set_facecolor('#ffffff')
g.ax_col_dendrogram.set_facecolor('#ffffff')
g.cax.tick_params(colors='#1f2937', labelsize=7)

g.fig.suptitle('Smartphone Feature Comparison', color='#1f2937', fontsize=13, fontweight='bold', y=1.02)
plt.show()