3D Bar Chart

Server Load Distribution

3D visualization of server load across time and nodes

Output
Server Load Distribution
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 time slots, 4 servers
time_slots = 6
servers = 4
xpos = np.arange(time_slots)
ypos = np.arange(servers)
xpos, ypos = np.meshgrid(xpos, ypos)
xpos = xpos.flatten()
ypos = ypos.flatten()
zpos = np.zeros_like(xpos)

dx = dy = 0.7
np.random.seed(42)
dz = np.random.randint(30, 95, size=24)

# Cyan gradient
colors = plt.cm.colors.LinearSegmentedColormap.from_list('', ['#27D3F5', '#4927F5'])
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('Time (hrs)', fontsize=11, color='#1f2937', labelpad=10)
ax.set_ylabel('Server', fontsize=11, color='#1f2937', labelpad=10)
ax.set_zlabel('Load %', fontsize=11, color='#1f2937', labelpad=10)
ax.set_title('Server Load Distribution', fontsize=14, color='#1f2937', fontweight='bold', pad=20)

ax.set_xticks(range(6))
ax.set_xticklabels(['0-4h', '4-8h', '8-12h', '12-16h', '16-20h', '20-24h'], fontsize=8)
ax.set_yticks(range(4))
ax.set_yticklabels(['Node1', 'Node2', 'Node3', 'Node4'])
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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