3D Bar Chart
Energy Consumption Grid
3D visualization of energy consumption across buildings and months
Output
Python
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure(figsize=(12, 8), facecolor='white')
ax = fig.add_subplot(111, projection='3d')
ax.set_facecolor('white')
# Data: 6 months, 5 buildings
months = 6
buildings = 5
xpos = np.arange(months)
ypos = np.arange(buildings)
xpos, ypos = np.meshgrid(xpos, ypos)
xpos = xpos.flatten()
ypos = ypos.flatten()
zpos = np.zeros_like(xpos)
dx = dy = 0.6
np.random.seed(123)
dz = np.random.randint(150, 450, size=30)
# Orange to yellow gradient
colors = plt.cm.colors.LinearSegmentedColormap.from_list('', ['#F54927', '#F5D327'])
bar_colors = [colors(v/max(dz)) for v in dz]
ax.bar3d(xpos, ypos, zpos, dx, dy, dz, color=bar_colors, alpha=0.9, edgecolor='#000000', linewidth=0.3)
ax.set_xlabel('Month', fontsize=11, color='#1f2937', labelpad=10)
ax.set_ylabel('Building', fontsize=11, color='#1f2937', labelpad=10)
ax.set_zlabel('kWh', fontsize=11, color='#1f2937', labelpad=10)
ax.set_title('Energy Consumption by Building', fontsize=14, color='#1f2937', fontweight='bold', pad=20)
ax.set_xticks(range(6))
ax.set_xticklabels(['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun'])
ax.set_yticks(range(5))
ax.set_yticklabels(['HQ', 'Lab', 'Warehouse', 'Office', 'Data Center'], fontsize=8)
ax.tick_params(colors='#000000', labelsize=9)
ax.xaxis.pane.fill = False
ax.yaxis.pane.fill = False
ax.zaxis.pane.fill = False
ax.xaxis.pane.set_edgecolor('#000000')
ax.yaxis.pane.set_edgecolor('#000000')
ax.zaxis.pane.set_edgecolor('#000000')
ax.grid(True, alpha=0.5, linewidth=0.5)
ax.xaxis._axinfo['grid']['color'] = '#000000'
ax.yaxis._axinfo['grid']['color'] = '#000000'
ax.zaxis._axinfo['grid']['color'] = '#000000'
ax.xaxis._axinfo['tick']['color'] = '#000000'
ax.yaxis._axinfo['tick']['color'] = '#000000'
ax.zaxis._axinfo['tick']['color'] = '#000000'
ax.xaxis.line.set_color('#000000')
ax.yaxis.line.set_color('#000000')
ax.zaxis.line.set_color('#000000')
plt.tight_layout()
plt.show()
Library
Matplotlib
Category
3D Charts
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