Create Interactive 2D and 3D Plots with Matplotlib in the Jupyter Notebook

To display how to easily plot 2D and 3D interactive plots with Matplotlib and its 3D in the Jupyter notebook

Table of Contents

1. 2D Interactive Plot

We can easily get zoom-able and resize-able plots using %matplotlib notebook magic in the notebook. It is the fastest and easiest way when you need to work with plots interactively. Let’s take a simple sine wave or sinusoid for example.

%matplotlib notebook 
# or widget

import numpy as np
import matplotlib.pyplot as plt

# define an array x of 32 uniformly spaced floating point
# values from 0 to 4π
x = np.linspace(0,4*np.pi,32)

# define y as the array containing the sine values from x
y = np.sin(x)

# make a plot 
fig = plt.figure(figsize=(5,3))
plt.plot(x, y)
plt.show()

The plot output looks as follows:

In the interactive plot, there are toolbar icons, including stop, home, backward, forward, pan, zoom and save.

Stop: Stop interactive plot mode
Home: Reset original view
Pan: Left button pans, Right button zooms x/y fixes axis, CTRL fixes aspect
Back: Back to previous view
Forward: Forward to next view
Zoom: Zoom to x/y fixes axis, CTRL fixes aspect
Save: Save as or download plot

However, the problem is that %matplotlib notebook failed to download figures if you use Chrome. This is because Chrome removed the ability for pages to open “data:”. Thus, we should use other browsers.

2. 3D Interactive Plot

To make the 3D plots interactive, we should install another library called ipympli.e. interactive python matplotlib. To install it directly in a Jupyter notebook, we can use the following command:

!pip install ipympl

The installation process looks as follows:

Collecting ipympl
  Downloading ipympl-0.9.2-py2.py3-none-any.whl (510 kB)
Requirement already satisfied: pillow in c:\users\sigmund\anaconda3\lib\site-packages (from ipympl) (9.0.1)
Requirement already satisfied: ipywidgets<9,>=7.6.0 in c:\users\sigmund\anaconda3\lib\site-packages (from ipympl) (7.6.5)
Requirement already satisfied: ipython<9 in c:\users\sigmund\anaconda3\lib\site-packages (from ipympl) (8.2.0)
Requirement already satisfied: ipython-genutils in 
.
.
.

>ipython<9->ipympl) (0.2.2)
Installing collected packages: ipympl
Successfully installed ipympl-0.9.2

The last three lines show that ipympl-0.9.2 was successfully installed. Then we create 3d plot using matplotlib in python with the following code snippet.

# for creating a responsive plot
%matplotlib notebook

# importing required libraries
import numpy as np  
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt

# creating random dataset
x = np.linspace(0,4*np.pi,1000)
y = np.sin(x) 
z = 15 * np.random.random(1000)

# creating figure
fig = plt.figure()
ax = Axes3D(fig)

# creating the plot
plot_scatter = ax.scatter(x, y, z,color='r')

# setting title and labels
ax.set_xlabel('x-axis')
ax.set_ylabel('y-axis')
ax.set_zlabel('z-axis')

# displaying the plot
plt.show()

The outcome looks as follows:

3. Online Course

If you are interested in learning Jupyter notebook in details, you are welcome to enrol one of my course Practical Jupyter Notebook from Beginner to Expert.

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