R packages for visualising spatial data

Throughout the #30DayChartChallenge I made most of my maps with R. This blog post details the R packages I find myself using most often when visualising spatial data.

How to make your own #RStats Wrapped!

Forget about Spotify Wrapped and make your own #RStats Wrapped instead! This blog post will show you how to find your most used functions and make a graphic with {ggplot2}!

30 Day Map Challenge 2022

The #30DayMapChallenge is a month-long mapping, cartography, and data visualization challenge aimed at the spatial community. Here are the things I’ve learnt from participating in the challenge for a second time.

Using functional analysis to model air pollution data in R

Let’s say you need to understand how your data changes within a day, and between different days. Functional analysis is one approach of doing just that so here’s how I applied functional analysis to some air pollution data using R!

Automatically deploying a Shiny app for browsing #RStats tweets with GitHub Actions

This tutorial blog will show you how to use GitHub actions to automatically update a data source and re-deploy a Shiny app, with an example Shiny application which uses {rtweet} to browse R-related tweets.

Introducing {PrettyCols}

An introduction to {PrettyCols} - a new R package containing aesthetically pleasing colour palettes that are compatible with {ggplot2}.