Visualization using Python

Basics

• Ten simple rules for better figures
  • [1]: Know Your Audience; [2]: Identify Your Message; [3]: Adapt the Figure to the Support Medium; [4]: Captions are not Optional; [5]: Do Not trust the Defaults; [6]: Use Color Effectively; [7]: Do Not Mislead the Reader; [8]: Avoid ‘‘Chartjunk’’; [9]: Message Trumps Beauty; [10]: Get the Right Tool
• Basic guide for plotting with Matplotlib
  • This is a very good introduction for Matplotlib

Great Examples

• Textbook Figures for Statistics, Data Mining, and Machine Learning in Astronomy

SciPy John Hunter Excellence in Plotting Contest

• The 2013 gallery - Many are astronomy related and excellent examples
• The 2014 gallery
• The 2015 gallery Link not working…
• The 2018 entries

Color and Colour

• Your Friendly Guide to Colors in Data Visualisation
  • Pretty much the only thing you need to read about color.
• Why rainbow colormap is harmful

Matplotlib

• Gallery of named colors in Matplotlib
• Gallery of colormaps in Matplotlib

Fancier and Better

• ColorBrewer2 - Interactive colormap builder
• Nippon Colors - Fancy traditional Japanese colors

Better Colormaps

• Palettable - Color palettes for Python
  • Really useful, with a lot of nice selections. Including color palettable from Wes Anderson movies.
• CMasher: Scientific colormaps for making accessible, informative and cmashing plots
  • “The colormaps in CMasher are all designed to be perceptually uniform sequential using the viscm package; most of them are color-vision deficiency (CVD; color blindness) friendly”
• Scientific Colour-Maps by Fabio Crameri
  • “Scientific colour-maps, like the colour maps devon, davos, oslo, and broc, are perceptually uniform, perceptually ordered, readable as B&W print and colour-vision-deficiency (CVD) friendly.”