3D Bar Chart
Product Reviews 3D
3D visualization of product review ratings by category and month
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 months, 6 categories
months = 4
categories = 6
xpos = np.arange(months)
ypos = np.arange(categories)
xpos, ypos = np.meshgrid(xpos, ypos)
xpos = xpos.flatten()
ypos = ypos.flatten()
zpos = np.zeros_like(xpos)
dx = dy = 0.6
np.random.seed(222)
dz = np.random.uniform(3.2, 4.9, size=24)
# Teal to green gradient
colors = plt.cm.colors.LinearSegmentedColormap.from_list('', ['#27D3F5', '#6CF527'])
bar_colors = [colors((v-3.2)/(4.9-3.2)) 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('Category', fontsize=11, color='#1f2937', labelpad=10)
ax.set_zlabel('Avg Rating', fontsize=11, color='#1f2937', labelpad=10)
ax.set_title('Product Review Ratings', fontsize=14, color='#1f2937', fontweight='bold', pad=20)
ax.set_xticks(range(4))
ax.set_xticklabels(['Jan', 'Feb', 'Mar', 'Apr'])
ax.set_yticks(range(6))
ax.set_yticklabels(['Electronics', 'Clothing', 'Home', 'Books', 'Sports', 'Beauty'], fontsize=8)
ax.tick_params(colors='#000000', labelsize=9)
ax.set_zlim(0, 5)
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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