Team Skills Matrix

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(42)

# Team members and skills
members = ['Alice', 'Bob', 'Carol', 'David', 'Eve', 'Frank', 'Grace', 'Henry']
skills = ['Python', 'SQL', 'ML/AI', 'Cloud', 'DevOps', 'Communication', 'Leadership', 'Problem Solving']

# Skill levels (1-5)
levels = np.random.randint(2, 5, (len(members), len(skills))) + np.random.rand(len(members), len(skills))
# Add specializations
levels[0, 0:3] += 1  # Alice: Data Science
levels[1, 3:5] += 1  # Bob: Infrastructure
levels[2, 5:8] += 1  # Carol: Soft skills
levels[3, 2] += 1.5  # David: ML specialist
levels = np.clip(levels, 1, 5)

df = pd.DataFrame(levels, index=members, columns=skills)

# NEON green-blue colormap
neon_skill = LinearSegmentedColormap.from_list('neon_skill', ['#f3f4f6', '#27F5B0', '#27D3F5', '#4927F5'])

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

sns.heatmap(df, cmap=neon_skill, annot=True, fmt='.1f', linewidths=2, linecolor='#ffffff',
            vmin=1, vmax=5, annot_kws={'size': 10, 'fontweight': '500'},
            cbar_kws={'shrink': 0.8, 'label': 'Skill Level (1-5)'}, ax=ax)

ax.set_title('Team Skills Assessment', color='#1f2937', fontsize=14, fontweight='bold', pad=15)
ax.set_xlabel('Skill', color='#1f2937', fontsize=11)
ax.set_ylabel('Team Member', color='#1f2937', fontsize=11)
ax.tick_params(colors='#374151', labelsize=10)
ax.set_xticklabels(ax.get_xticklabels(), rotation=30, ha='right')

plt.tight_layout()
plt.show()