API Performance Heatmap

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)

# Hours and days
hours = [f'{h:02d}:00' for h in range(24)]
days = ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']

# Response times (ms)
times = np.random.randint(50, 150, (24, 7))
# Add patterns
times[9:18, :5] += 50  # Business hours higher
times[12:14, :5] += 30  # Lunch peak
times[0:6, :] -= 30    # Night low
times = np.clip(times, 20, 250)

df = pd.DataFrame(times, index=hours, columns=days)

# NEON performance colormap (green=fast, red=slow)
neon_perf = LinearSegmentedColormap.from_list('neon_perf', ['#6CF527', '#F5B027', '#F5276C'])

fig, ax = plt.subplots(figsize=(8, 9), facecolor='#ffffff')
ax.set_facecolor('#ffffff')

sns.heatmap(df, cmap=neon_perf, linewidths=1, linecolor='#ffffff',
            cbar_kws={'shrink': 0.5, 'label': 'Response Time (ms)'}, ax=ax)

ax.set_title('API Response Time Heatmap', color='#1f2937', fontsize=14, fontweight='bold', pad=15)
ax.set_xlabel('Day of Week', color='#1f2937', fontsize=11)
ax.set_ylabel('Hour', color='#1f2937', fontsize=11)
ax.tick_params(colors='#374151', labelsize=9)

# Add SLA threshold annotation
ax.text(0.98, 0.02, 'SLA: <200ms', transform=ax.transAxes, ha='right', va='bottom',
        fontsize=10, color='#F5276C', fontweight='bold',
        bbox=dict(boxstyle='round', facecolor='#ffffff', edgecolor='#F5276C'))

plt.tight_layout()
plt.show()