Heatmap

Error Code Heatmap

Dark theme heatmap showing error frequency by service

Output
Error Code Heatmap
Python
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap
from matplotlib.patches import FancyBboxPatch

fig, ax = plt.subplots(figsize=(12, 8), facecolor='#ffffff')
ax.set_facecolor('#ffffff')

np.random.seed(42)
error_codes = ['400', '401', '403', '404', '500', '502', '503']
services = ['API', 'Auth', 'CDN', 'DB', 'Cache']
errors = np.random.poisson(5, (len(services), len(error_codes)))

colors = ['#1e293b', '#7f1d1d', '#dc2626', '#f87171', '#fecaca']
cmap = LinearSegmentedColormap.from_list('error', colors, N=256)

cell_w, cell_h = 0.88, 0.82
for i in range(len(services)):
    for j in range(len(error_codes)):
        val = errors[i, j]
        rect = FancyBboxPatch((j - cell_w/2, i - cell_h/2), cell_w, cell_h,
                               boxstyle="round,pad=0.02,rounding_size=0.12",
                               facecolor=cmap(val/errors.max()), edgecolor='#e2e8f0', linewidth=1.5)
        ax.add_patch(rect)
        if val > 0:
            ax.text(j, i, str(val), ha='center', va='center', color='#1e293b', fontsize=10, fontweight='bold')

ax.set_xlim(-0.5, len(error_codes)-0.5)
ax.set_ylim(-0.5, len(services)-0.5)
ax.set_aspect('equal')
ax.invert_yaxis()
ax.set_xticks(range(len(error_codes)))
ax.set_yticks(range(len(services)))
ax.set_xticklabels(error_codes, color='#64748b', fontsize=10, fontweight='500', family='monospace')
ax.set_yticklabels(services, color='#1e293b', fontsize=10, fontweight='500')

sm = plt.cm.ScalarMappable(cmap=cmap, norm=plt.Normalize(0, errors.max()))
cbar = plt.colorbar(sm, ax=ax, shrink=0.8, pad=0.02)
cbar.set_label('Error Count', color='#1e293b', fontsize=11)
cbar.outline.set_edgecolor('#e2e8f0')
plt.setp(plt.getp(cbar.ax.axes, 'yticklabels'), color='#64748b')

for spine in ax.spines.values(): spine.set_visible(False)
ax.tick_params(length=0)
ax.set_title('HTTP Error Distribution by Service', fontsize=18, color='#1e293b', fontweight='bold', pad=20)
plt.tight_layout()
plt.show()
Library

Matplotlib

Category

Heatmaps & Density

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