Creating 3D Plots in Matplotlib and Removing White Border Margin.

In this tutorial, we will explore how to create stunning 3D plots using Matplotlib, a popular Python data visualization library (Matplotlib Removing White Border Margin). We’ll also delve into the techniques for removing the white borders around your 3D graphs, enhancing the visual appeal of your plots.

Section 1: Introduction to Matplotlib and 3D Plots

Matplotlib is a versatile library for creating high-quality visualizations in Python. It supports various plot types, including 3D plots, which are particularly useful for visualizing complex data in three dimensions. Let’s start by introducing Matplotlib and how to create 3D plots.

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

# Create a figure and 3D axes
fig = plt.figure(figsize=(10, 8))
ax = fig.add_subplot(111, projection='3d')

# Create some 3D data
u = np.linspace(0, 2 * np.pi, 100)
v = np.linspace(0, np.pi, 100)
x = 10 * np.outer(np.cos(u), np.sin(v))
y = 10 * np.outer(np.sin(u), np.sin(v))
z = 10 * np.outer(np.ones(np.size(u)), np.cos(v))

# Plot the 3D surface
ax.plot_surface(x, y, z, rstride=4, cstride=4, color='b')

# Turn off the axis labels and ticks

# Show the plot

Creating 3D Plots in Matplotlib and Removing White Border Margin
Creating 3D Plots in Matplotlib and Removing White Border Margin

Section 2: Removing White Borders

By default, Matplotlib may add white borders around your 3D plots. These borders can be distracting and affect the aesthetics of your visualization. Fortunately, there are two methods for removing these white borders:

Method 1: Adjusting Axes Limits

To remove white borders inside the axes, you can modify the x, y, and z limits using the ax.set_xlim(), ax.set_ylim(), and ax.set_zlim() functions. This allows you to control the visible range of your plot.

# Adjusting axes limits
ax.set_xlim(-8, 8)
ax.set_ylim(-8, 8)
ax.set_zlim(-8, 8)

Method 2: Subplot Margins Adjustment

Alternatively, you can remove whitespace outside the axes by adjusting the subplot margins using fig.subplots_adjust(). This method ensures that your plot takes up the entire figure area without unnecessary white space.

# Subplot margins adjustment
fig.subplots_adjust(left=0, right=1, bottom=0, top=1)


Creating 3D plots in Matplotlib is a powerful way to visualize complex data in three dimensions. To enhance the visual appeal of your plots, it’s essential to remove any distracting white borders. You can achieve this by adjusting axes limits or using subplot margins adjustment, as demonstrated in this tutorial.

We hope this tutorial has been helpful in improving your 3D plots. Feel free to experiment with these techniques to create visually stunning visualizations in your Python projects.

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