Viewing angle control in Matplotlib

Introduction

Viewing angle control helps you see 3D plots from different sides. It makes understanding shapes and data easier.

You want to explore a 3D scatter plot to see clusters from different angles.

You need to show a 3D surface plot clearly in a presentation.

You want to compare how a 3D bar chart looks from the front and the side.

You are analyzing 3D data and want to find hidden patterns by rotating the view.

Syntax

Matplotlib

ax.view_init(elev=angle1, azim=angle2)

elev sets the vertical angle (up and down).

azim sets the horizontal angle (left and right).

Examples

Set the view to 30 degrees up and 45 degrees to the right.

Matplotlib

ax.view_init(elev=30, azim=45)

Look straight down from above the plot.

Matplotlib

ax.view_init(elev=90, azim=0)

Look at the plot from the side horizontally.

Matplotlib

ax.view_init(elev=0, azim=90)

Sample Program

This code creates a 3D surface plot of a wave pattern. The view is set to 45 degrees up and 60 degrees to the right so you can see the shape clearly.

Matplotlib

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

# Create sample data
x = np.linspace(-5, 5, 100)
y = np.linspace(-5, 5, 100)
X, Y = np.meshgrid(x, y)
Z = np.sin(np.sqrt(X**2 + Y**2))

# Plot a 3D surface
ax.plot_surface(X, Y, Z, cmap='viridis')

# Set viewing angle
ax.view_init(elev=45, azim=60)

plt.show()

Important Notes

You can change the viewing angle anytime to explore your 3D plot.

Angles are in degrees, where elev=0 means looking from the side, elev=90 means looking from above.

Try different angles to find the best view for your data.

Summary

Viewing angle control changes how you see 3D plots.

Use ax.view_init(elev, azim) to set vertical and horizontal angles.

Adjust angles to understand your 3D data better.