Quick Learning: Matplotlib Tutorial (compatible with Google Colab / Windows / macOS / Linux) by nitta@tsuda.ac.jp

Learning Policy

Since matplotlib is a flexible system, it can be written in various ways, which confuses beginners. In this article, we will explain how to write matplotlib programming easily according to the small number of cardinal rules, that is, a method with a wide range of applications but less confusion. Being able to solve various problems with one method is the fastest way to improve your matplotlib programming.

matplotlib tutorial (1): Understanding the Coordinate System (Axes Object) ... html ipynb
matplotlib tutorial (2): Drawing Line Graphs ... html ipynb
matplotlib tutorial (3): Using Japanese Font ... html ipynb
matplotlib tutorial (4): Title and Axis ... html ipynb
matplotlib tutorial (5): Drawing Texts in the Graph ... html ipynb
matplotlib tutorial (6): Scatter Diagram, Contour Lines, Filling ... html ipynb
matplotlib tutorial (7): Saving / loading / Displaying of Images ... html ipynb
matplotlib tutorial (8): Axis (2) ... html ipynb
matplotlib tutorial (9): Bar Graph ... html ipynb
matplotlib tutorial (10): Pi Chart / Circle Graph ... html ipynb
matplotlib tutorial (11): 3D Graph ... html ipynb
matplotlib tutorial (12): Bar Graph (2) ... html ipynb
matplotlib tutorial (13): Animation JSAnimation (compatible with Google Colab) ... html ipynb
matplotlib tutorial (14): Animation (2) OpenAI Gym Envs (compatible with Google Colab) ... html ipynb
matplotlib tutorial (15): Understanding the Coordinate System (Axes Object) (2) ... html ipynb

Compatibility Check

The versions of OS and python packages when checking the compatibilities are as follows. html ipynb

Platform	OS version	python	matplotlib	numpy	tensorflow	gym
Google Colab	Ubuntu 18.04	3.7.13	3.2.2	1.21.6	2.8.2	0.17.3
Windows	Windows 10.0.19043	3.10.4	3.5.2	1.23.1	2.9.1	0.24.1
Mac (intel)	macOS 12.4 Monterey	3.9.12	3.5.2	1.23.1	2.9.1	0.24.1
Mac (arm64)	macOS 12.4 Monterey	3.8.13 miniforge3	3.5.2	1.23.1	2.9.2 tensorflow-metal	0.25.0
Linux (intel)	Ubuntu 22.04	3.10.4	3.5.2	1.23.1	2.9.1	0.24.1

Known Issues

On Linux (intel), some errors occur at the OpenAI gym in "matplotlib_tutorial_14{,_en}.ipynb". (Jul/12/2022)
On macOS (arm64), some errors occur at the anim.save('*.mp4') in "matplotlib_tutorial_13{,_en}.ipynb". (Jul/12/2022)

Execution Environment on Google Colabe

The codes below can be executed in the default state.

Execution Environment on Anaconda on Windows / macOS / Linux

Create a Python virtual environment with the packages installed.

"Anaconda Prompt"(on Windows) or "Terminal"(on macOS or Linux)

(base) nitta$ conda create -n myenv python jupyter  
(base) nitta$ conda activate myenv  
(myenv) nitta$ pip install numpy  
(myenv) nitta$ pip install matplotlib  
(myenv) nitta$ pip install tensorflow  
(myenv) nitta$ pip install --user pygame  
(myenv) nitta$ pip install gym  
(myenv) nitta$ conda deactivate  
(base) nitta$

Execute jupyter notebook.

"Anaconda Prompt"(on Windows) or "Terminal" (on macOS or Linux)

(base) nitta$ conda activate myenv  
(myenv) nitta$ jupyter notebook

OS Depencencies

On macOS (intel), ffmpeg needs to be installed to save animations as files. You can install it with the "brew intall ffmpeg" command using homebrew.

On Linux(intel) , ffmpeg needs to be installed to save animations as files. You can install it with the "sudo apt update; sudo apt intall ffmpeg" command on Utuntu Linux.