Visualising data

Philosophy and psychology of good plots

July 4, 2016 — November 21, 2023

computers are awful
faster pussycat
generative art
making things
photon choreography
Figure 1

A grab-bag of links about making data visually comprehensible. For now this is mostly a lift of people I want to link to, but I might also share some insight into good communicative graphic design if, heaven forfend, I end up needing to pretend to be a graphic designer in some dire strait. A weird corner of this discipline is the specialisation, data dashboards, which appeals to executives and thus has money in it, so has its own notebook.

1 Resources

2 Practitioners

3 References

Heer, Bostock, and Ogievetsky. 2010. A Tour Through the Visualization Zoo.” Queue.
Lucchesi, Kuhnert, and Wikle. 2021. Vizumap: An R Package for Visualising Uncertainty in Spatial Data.” Journal of Open Source Software.
McInnes, Healy, and Melville. 2018. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.” arXiv:1802.03426 [Cs, Stat].
Olah, Mordvintsev, and Schubert. 2017. Feature Visualization.” Distill.
Wickham. 2010. Ggplot2: Elegant Graphics for Data Analysis (Use R!).