3D Bar Chart
Inventory Levels 3D
3D visualization of inventory levels across warehouses and product lines
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: 4 warehouses, 5 product lines
warehouses = 4
products = 5
xpos = np.arange(warehouses)
ypos = np.arange(products)
xpos, ypos = np.meshgrid(xpos, ypos)
xpos = xpos.flatten()
ypos = ypos.flatten()
zpos = np.zeros_like(xpos)
dx = dy = 0.6
np.random.seed(444)
dz = np.random.randint(500, 2500, size=20)
# Yellow to lime gradient
colors = plt.cm.colors.LinearSegmentedColormap.from_list('', ['#D3F527', '#27F5B0'])
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('Warehouse', fontsize=11, color='#1f2937', labelpad=10)
ax.set_ylabel('Product Line', fontsize=11, color='#1f2937', labelpad=10)
ax.set_zlabel('Units', fontsize=11, color='#1f2937', labelpad=10)
ax.set_title('Inventory Levels by Warehouse', fontsize=14, color='#1f2937', fontweight='bold', pad=20)
ax.set_xticks(range(4))
ax.set_xticklabels(['West', 'East', 'North', 'South'])
ax.set_yticks(range(5))
ax.set_yticklabels(['Raw', 'WIP', 'Finished', 'Returns', 'Spare'], fontsize=9)
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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