Database Query Heatmap

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap
from matplotlib.patches import FancyBboxPatch

fig, ax = plt.subplots(figsize=(14, 7), facecolor='#ffffff')
ax.set_facecolor('#ffffff')

np.random.seed(42)
tables = ['users', 'orders', 'products', 'sessions', 'logs']
hours = [f'{h:02d}:00' for h in range(0, 24, 2)]
queries = np.random.gamma(5, 100, (len(tables), len(hours)))

colors = ['#1e293b', '#7c2d12', '#ea580c', '#fb923c', '#fed7aa']
cmap = LinearSegmentedColormap.from_list('query', colors, N=256)

cell_w, cell_h = 0.88, 0.82
for i in range(len(tables)):
    for j in range(len(hours)):
        val = queries[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/queries.max()), edgecolor='#e2e8f0', linewidth=1.5)
        ax.add_patch(rect)

ax.set_xlim(-0.5, len(hours)-0.5)
ax.set_ylim(-0.5, len(tables)-0.5)
ax.set_aspect('equal')
ax.invert_yaxis()
ax.set_xticks(range(len(hours)))
ax.set_yticks(range(len(tables)))
ax.set_xticklabels(hours, rotation=45, ha='right', color='#64748b', fontsize=9, fontweight='500')
ax.set_yticklabels(tables, color='#1e293b', fontsize=10, fontweight='500', family='monospace')

sm = plt.cm.ScalarMappable(cmap=cmap, norm=plt.Normalize(0, queries.max()))
cbar = plt.colorbar(sm, ax=ax, shrink=0.8, pad=0.02)
cbar.set_label('Queries/sec', 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('Database Query Load by Table', fontsize=18, color='#1e293b', fontweight='bold', pad=20)
plt.tight_layout()
plt.show()