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rougier/scientific-visualization-book

★ 11,255PythonAudience · researcherComplexity · 2/5Setup · moderate

TLDR

A free, open-access book and code repository teaching researchers and students how to create publication-quality scientific figures using Python and Matplotlib, covering layout, color, 3D figures, and animation.

Mindmap

mindmap
  root((repo))
    Book parts
      Matplotlib fundamentals
      Figure design
      Advanced topics
      Showcase examples
    Topics
      Coordinate systems
      Color and typography
      3D figures
      Animation
    Resources
      Free PDF on HAL
      Full source code
      Printed edition
    Audience
      Researchers
      Students
      Data analysts
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Code map

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Things people build with this

USE CASE 1

Create publication-ready charts and graphs for scientific papers using Matplotlib with proper typography and color choices

USE CASE 2

Build animated or 3D visualizations for academic presentations by following the book's advanced chapters and included source code

USE CASE 3

Apply Matplotlib's styling system to keep all figures in a paper visually consistent

USE CASE 4

Copy finished showcase examples from the repository as starting points for your own scientific figures

Tech stack

PythonMatplotlib

Getting it running

Difficulty · moderate Time to first run · 30min

Building the full book locally requires Ubuntu with specific LaTeX and Python dependencies, running individual code examples only needs Python and Matplotlib.

In plain English

This repository holds the source for an open-access book titled "Scientific Visualization: Python + Matplotlib," written by Nicolas P. Rougier and published in November 2021. The book teaches how to create high-quality scientific figures using Matplotlib, a Python library for drawing charts and graphs, and is aimed at researchers, students, and data analysts who want publication-ready visuals. The book is organized into four parts. The first covers the core structure of Matplotlib: how figures are composed, how coordinate systems work, what scales and projections are available, and how typography and color choices affect the result. The second part focuses on actually designing figures, starting with rules for better visuals, then moving into Matplotlib's styling system, figure layout, the range of available plot types, and decorative elements. The third part addresses more advanced topics: 3D figures, optimization, and animation. The fourth part is a collection of finished showcase examples. The full book is available for free as a PDF, hosted on a French open-access academic archive called HAL. All source code for the examples is included in this repository. A printed edition is available on Amazon for $49. The repository also contains scripts for building the book locally on Ubuntu if you want to compile it yourself. The author accepts tips and sponsorships through PayPal, GitHub Sponsors, and Liberapay for those who want to support continued work on the project.

Copy-paste prompts

Prompt 1
Using the scientific-visualization-book examples, how do I set up a Matplotlib figure with custom typography and a color palette suitable for a journal submission?
Prompt 2
I want to create a 3D animated figure in Matplotlib for my research presentation, which section and code examples in the scientific-visualization-book cover this?
Prompt 3
How do I use Matplotlib's styling system to apply consistent visual design across all figures in my paper, following the scientific-visualization-book approach?
Prompt 4
How do I build the scientific-visualization-book locally on Ubuntu to get the full compilable PDF, and what dependencies do I need?
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