Scientific Visualization: Python + Matplotlib

Overview

Scientific Visualization: Python + Matplotlib

Nicolas P. Rougier, Bordeaux, November 2021.

Front cover

The Python scientific visualisation landscape is huge. It is composed of a myriad of tools, ranging from the most versatile and widely used down to the more specialised and confidential. Some of these tools are community based while others are developed by companies. Some are made specifically for the web, others are for the desktop only, some deal with 3D and large data, while others target flawless 2D rendering. In this landscape, Matplotlib has a very special place. It is a versatile and powerful library that allows you to design very high quality figures, suitable for scientific publishing. It also offers a simple and intuitive interface as well as an object oriented architecture that allows you to tweak anything within a figure. Finally, it can be used as a regular graphic library in order to design non‐scientific figures. This book is organized into four parts. The first part considers the fundamental principles of the Matplotlib library. This includes reviewing the different parts that constitute a figure, the different coordinate systems, the available scales and projections, and we’ll also introduce a few concepts related to typography and colors. The second part is dedicated to the actual design of a figure. After introducing some simple rules for generating better figures, we’ll then go on to explain the Matplotlib defaults and styling system before diving on into figure layout organization. We’ll then explore the different types of plot available and see how a figure can be ornamented with different elements. The third part is dedicated to more advanced concepts, namely 3D figures, optimization & animation. The fourth and final part is a collection of showcases.

Read the book

You can read the book PDF (95Mo, preferred site) that is open access and hosted on HAL which is a French open archive for academics. Up to date version is also available on GitHub here. Sources for the book (including code examples) are available at github.com/rougier/scientific-visualization-book.

Buy the book

If you want to buy the book, you can order a printed edition at amazon.com for 49$. If you want to support or sponsor my future work on Python (and Emacs), you can use paypal, github or liberapay.

See also

Book gallery

Owner
Nicolas P. Rougier
Researcher in computational and cognitive neuroscience supporting open source, open access and open science.
Nicolas P. Rougier
A GUI for Pandas DataFrames

PandasGUI A GUI for analyzing Pandas DataFrames. Demo Installation Install latest release from PyPi: pip install pandasgui Install directly from Githu

Adam 2.8k Jan 03, 2023
A python package for animating plots build on matplotlib.

animatplot A python package for making interactive as well as animated plots with matplotlib. Requires Python = 3.5 Matplotlib = 2.2 (because slider

Tyler Makaro 394 Dec 18, 2022
Regress.me is an easy to use data visualization tool powered by Dash/Plotly.

Regress.me Regress.me is an easy to use data visualization tool powered by Dash/Plotly. Regress.me.-.Google.Chrome.2022-05-10.15-58-59.mp4 Get Started

Amar 14 Aug 14, 2022
🐍PyNode Next allows you to easily create beautiful graph visualisations and animations

PyNode Next A complete rewrite of PyNode for the modern era. Up to five times faster than the original PyNode. PyNode Next allows you to easily create

ehne 3 Feb 12, 2022
Here are my graphs for hw_02

Let's Have A Look At Some Graphs! Graph 1: State Mentions in Congressperson's Tweets on 10/01/2017 The graph below uses this data set to demonstrate h

7 Sep 02, 2022
I'm doing Genuary, an aritifiacilly generated month to build code that make beautiful things

Genuary 2022 I'm doing Genuary, an aritifiacilly generated month to build code that make beautiful things. Every day there is a new prompt for making

Joaquín Feltes 1 Jan 10, 2022
This tool is designed to help administrators get an overview of their Active Directory structure.

This tool is designed to help administrators get an overview of their Active Directory structure. In the group view you can see all elements of an AD (OU, USER, GROUPS, COMPUTERS etc.). In the user v

deexno 2 Oct 30, 2022
YOPO is an interactive dashboard which generates various standard plots.

YOPO is an interactive dashboard which generates various standard plots.you can create various graphs and charts with a click of a button. This tool uses Dash and Flask in backend.

ADARSH C 38 Dec 20, 2022
Simple spectra visualization tool for astronomers

SpecViewer A simple visualization tool for astronomers. Dependencies Python = 3.7.4 PyQt5 = 5.15.4 pyqtgraph == 0.10.0 numpy = 1.19.4 How to use py

5 Oct 07, 2021
PanGraphViewer -- show panenome graph in an easy way

PanGraphViewer -- show panenome graph in an easy way Table of Contents Versions and dependences Desktop-based panGraphViewer Library installation for

16 Dec 17, 2022
Functions for easily making publication-quality figures with matplotlib.

Data-viz utils 📈 Functions for data visualization in matplotlib 📚 API Can be installed using pip install dvu and then imported with import dvu. You

Chandan Singh 16 Sep 15, 2022
A deceptively simple plotting library for Streamlit

🍅 Plost A deceptively simple plotting library for Streamlit. Because you've been writing plots wrong all this time. Getting started pip install plost

Thiago Teixeira 192 Dec 29, 2022
Some useful extensions for Matplotlib.

mplx Some useful extensions for Matplotlib. Contour plots for functions with discontinuities plt.contour mplx.contour(max_jump=1.0) Matplotlib has pro

Nico Schlömer 519 Dec 30, 2022
Mapomatic - Automatic mapping of compiled circuits to low-noise sub-graphs

mapomatic Automatic mapping of compiled circuits to low-noise sub-graphs Overvie

Qiskit Partners 27 Nov 06, 2022
A pandas extension that solves all problems of Jalai/Iraninan/Shamsi dates

Jalali Pandas Extentsion A pandas extension that solves all problems of Jalai/Iraninan/Shamsi dates Features Series Extenstion Convert string to Jalal

51 Jan 02, 2023
NW 2022 Hackathon Project by Angelique Clara Hanzel, Aryan Sonik, Damien Fung, Ramit Brata Biswas

Spiral-Data-Visualizer NW 2022 Hackathon Project by Angelique Clara Hanzell, Aryan Sonik, Damien Fung, Ramit Brata Biswas Description This project vis

Damien Fung 2 Jan 16, 2022
Python ts2vg package provides high-performance algorithm implementations to build visibility graphs from time series data.

ts2vg: Time series to visibility graphs The Python ts2vg package provides high-performance algorithm implementations to build visibility graphs from t

Carlos Bergillos 26 Dec 17, 2022
📊📈 Serves up Pandas dataframes via the Django REST Framework for use in client-side (i.e. d3.js) visualizations and offline analysis (e.g. Excel)

📊📈 Serves up Pandas dataframes via the Django REST Framework for use in client-side (i.e. d3.js) visualizations and offline analysis (e.g. Excel)

wq framework 1.2k Jan 01, 2023
Squidpy is a tool for the analysis and visualization of spatial molecular data.

Squidpy is a tool for the analysis and visualization of spatial molecular data. It builds on top of scanpy and anndata, from which it inherits modularity and scalability. It provides analysis tools t

Theis Lab 251 Dec 19, 2022
cqMore is a CadQuery plugin based on CadQuery 2.1.

cqMore (under construction) cqMore is a CadQuery plugin based on CadQuery 2.1. Installation Please use conda to install CadQuery and its dependencies

Justin Lin 36 Dec 21, 2022