scientific visualization / Matplotlib book
Open-access book teaching scientific visualization with Python and Matplotlib, focused on producing publication-quality figures.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Fast interactive/real-time plotting stack; choose it for live or GUI-embedded data instead of static publication figures.
Fast data visualization and GUI tools for scientific / engineering applications
VTK/Numpy-based 3D scientific visualization; choose it for interactive 3D data analysis instead of Matplotlib.
A python module for scientific analysis of 3D data based on VTK and Numpy
A broader data-science handbook with Matplotlib chapters; choose it for an all-in-one Python data-science resource.
Python Data Science Handbook: full text in Jupyter Notebooks
High-level statistical plotting API; choose it for quick statistical graphics over low-level Matplotlib.
Statistical data visualization in Python
OpenGL-based GPU visualization; choose it for high-performance interactive 2D/3D graphics instead of static Matplotlib.
Python+Numpy+OpenGL: fast, scalable and beautiful scientific visualization
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
A formatting toolkit for CNS-journal styles; choose it when you just need journal-specific layout instead of reading the full book.
🎨 Toolkit for generating publication-quality plots for Cell, Nature and Science journals
A compact quick-reference cheat sheet; useful for lookup but far less detailed than the book.
simple overview of python, numpy, scipy, matplotlib functions that are useful for scientific work
Scientific colormap collection; choose it for perceptually-uniform colormaps without designing your own.
Scientific colormaps for making accessible, informative and 'cmashing' plots
Figure size/font configuration pack; choose it for quick journal-compliant layouts instead of reading styling advice.
Figure sizes, font sizes, fonts, and more configurations at minimal overhead. Fix your journal papers, conference proceedings, and other scientific publications.
Matplotlib style sheets for papers/theses; choose them for ready-made clean formatting instead of learning the book's styling tips.
Matplotlib style sheets to nicely format figures for scientific papers, thesis and presentations while keeping them fully editable in Adobe Illustrator.
Specialized wind-rose plotting library; choose it when you only need meteorological wind diagrams.
A Python Matplotlib, Numpy library to manage wind data, draw windrose (also known as a polar rose plot), draw probability density function and fit Weibull distribution
Ready-made Matplotlib science styles; choose them for quick publication-styled figures without reading the book.
Matplotlib styles for scientific plotting
Does the same job, but ships as an app. Useful to a person, not swappable into a codebase.
An AI agent tool that restyles plots to match a target paper; choose it for automated styling, not as a reusable library.
An Automated AI Agent Tool for Plotting Your Data in Any Paper's Figure Style.
These projects were analysed and named scientific-visualization-book among their alternatives. The relationship is not symmetric — how scientific-visualization-book rates them is a separate judgement, made when scientific-visualization-book is analysed in its own right.
calls scientific-visualization-book “narrower: matplotlib/scientific-visualization book, not the whole stack”
Python Data Science Handbook: full text in Jupyter Notebooks