In data visualisations, colours are often used to show values or categories of data. However, sometimes you might not be able to or want to use colour. This blog post discusses some tips for designing better visualisations when you’re restricted to a monochrome palette.

Whether you’re building data visualisations or generative art, at some point you will likely need to consider which colours to use in R. This blog post describes different ways to define colours, how to make good choices about colour palettes, and ways to generate your own colour schemes.

The {messy} R package takes a clean dataset, and randomly adds mess to create data more similar to that which you’d find in the real world. This is an easy way for educators to create data sets that give students the opportunity to practice their data wrangling skills without having to change all of their examples.

A blog post about some of the things that have helped me in getting comfortable talking about tech (although hopefully some of the advice is also useful for non-tech talks!).

After running the ‘Parameterized plots and reports with R and Quarto’ workshop as part of the R/Pharma 2024 Conference, there were a few questions that we didn’t get the chance to answer. This blog post aims to answer some of them.

There are many reasons why learning about generative art can be beneficial for data scientists. This blog post will explain what generative art is, where to find some inspiration, and how to start creating your own generative art systems.