Energy Consumption 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, 8), facecolor='#ffffff')
ax.set_facecolor('#ffffff')

np.random.seed(42)
zones = ['Building A', 'Building B', 'Building C', 'Data Center', 'Factory']
months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
energy = np.random.gamma(5, 200, (len(zones), len(months)))
energy[3, :] *= 3

colors = ['#1e293b', '#7c3aed', '#a855f7', '#fbbf24', '#fef3c7']
cmap = LinearSegmentedColormap.from_list('modern', colors, N=256)

cell_width = 0.88
cell_height = 0.82
for i in range(len(zones)):
    for j in range(len(months)):
        val = energy[i, j]
        color = cmap(val / energy.max())
        rect = FancyBboxPatch((j - cell_width/2, i - cell_height/2), 
                               cell_width, cell_height,
                               boxstyle="round,pad=0.02,rounding_size=0.12",
                               facecolor=color, edgecolor='#e2e8f0', linewidth=1.5)
        ax.add_patch(rect)
        

ax.set_xlim(-0.5, len(months) - 0.5)
ax.set_ylim(-0.5, len(zones) - 0.5)
ax.set_aspect('equal')
ax.invert_yaxis()

ax.set_xticks(range(len(months)))
ax.set_yticks(range(len(zones)))
ax.set_xticklabels(months, color='#64748b', fontsize=9, fontweight='500')
ax.set_yticklabels(zones, color='#1e293b', fontsize=11, fontweight='500')

sm = plt.cm.ScalarMappable(cmap=cmap, norm=plt.Normalize(vmin=0, vmax=energy.max()))
cbar = plt.colorbar(sm, ax=ax, shrink=0.8, aspect=30, pad=0.02)
cbar.set_label('Energy (MWh)', color='#1e293b', fontsize=11, fontweight='500')
cbar.ax.yaxis.set_tick_params(color='#64748b')
plt.setp(plt.getp(cbar.ax.axes, 'yticklabels'), color='#64748b')
cbar.outline.set_edgecolor('#e2e8f0')

for spine in ax.spines.values():
    spine.set_visible(False)

ax.set_title('Monthly Energy Consumption by Zone', fontsize=18, color='#1e293b', fontweight='bold', pad=20)
ax.tick_params(length=0)
plt.tight_layout()
plt.show()