A blog about all things visualisation, data science, and open source software. Some of these blog posts can also be found on R-bloggers, and many have been featured in the R Weekly highlights.
After another 52 data visualisations created for #TidyTuesday, it’s time for the annual round-up! Read this blog post for some interesting R packages discovered, a few new I’ve tricks learnt, and the data visualisations I’d like to do again.
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.
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}!
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.
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!
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.