Heatmap

Sales Performance Heatmap

Dark theme heatmap showing sales by region and product

Output
Sales Performance 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)
regions = ['North', 'South', 'East', 'West', 'Central']
products = ['Product A', 'Product B', 'Product C', 'Product D', 'Product E', 'Product F']
data = np.random.randint(50, 500, (len(regions), len(products)))

colors = ['#1e293b', '#164e63', '#0891b2', '#c026d3', '#f5d0fe']
cmap = LinearSegmentedColormap.from_list('sales', colors, N=256)

cell_w, cell_h = 0.88, 0.82
for i in range(len(regions)):
    for j in range(len(products)):
        val = data[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/500), edgecolor='#e2e8f0', linewidth=1.5)
        ax.add_patch(rect)
        ax.text(j, i, f'${val}K', ha='center', va='center', color='#1e293b', fontsize=9, fontweight='bold')

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

sm = plt.cm.ScalarMappable(cmap=cmap, norm=plt.Normalize(0, 500))
cbar = plt.colorbar(sm, ax=ax, shrink=0.8, pad=0.02)
cbar.set_label('Sales ($K)', 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('Sales by Region & Product', fontsize=18, color='#1e293b', fontweight='bold', pad=20)
plt.tight_layout()
plt.show()
Library

Matplotlib

Category

Heatmaps & Density

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