All the useful websites!
I have already emailed these Dataviz resources to countless scientists - high time to finally set up a centralised collection of to all websites!
The links are organised by the different aspects of creating scientific data figures: 1. Choosing a chart, 2. text, 3. layouts, 4. colours. There are also links to special use cases and a bit of entertainment.
Choosing charts
- Severino Ribecca DataViz Catalogue
- Yan Holz Python Graph Gallery - also available for R!
- Ferdio’s illustrated guide
Further reading: Beyond bar and line plots
Text (replace text with images)
Some general pictogram resources:
- Fontawesome, use with attribution
- The Nounproject - use with attribution, registration necessary
- SVG repo General Pictogram collection
- Flaticon General Pictogram collectionhttps://www.flaticon.com/
- Iconduck General Pictogram collectionhttps://iconduck.com/
- Simpleicons General Pictogram collectionhttps://simpleicons.org/
Biology/Science
- Simon Dürr’s bioicon collection
- Icons of all animals and plants etc
- General science icons
- Science/chemistry icons:
- SCIDRAW a repository of free SVG cartoons for science supported by the Sainsbury Wellcome Centre, CC-BY
Medicine
Layout
Find inspiring Layouts in Will Timmins-Stahl BMJ Infografics
Color
- Color Brewer: Pick color schemes for data
- WebAIM Check if contrast of foreground and background colors are good (and other accessibility issues)
- Color palette designer
- Pick color from image icolorpalette.com/color-palette-from-images
- XKCD color study about color names XKCD
- Lisa Rost, datadrapper: Pick beautiful colors for your charts
Specials
Graphical Abstracts
My article about Graphical Abstracts (without Biorender)
Resources for image data
Tables
Check out my previous blog.
Fun with numbers
- How good are you at judging R-values? GuessTheCorrelation
- A funny tool to make up your data
- Eyeballing game: guess angles in data
- Clearly Nicolas cage is causing suicides: Correlation/Causation
Slides from an introductory talk
- intro to why we visualize
- tips: how not to lie with charts
- exercises for improving poor charts