Published: May 22, 2025
From a purely design aspect, Quarto's standard output for PowerPoint falls short. You're limited to seven layout options, with the most complicated being "Two Content". The {officer} R package provides a great alternative, for those seeking total control and customisation.
Published: November 23, 2023
The `theme()` command from {ggplot2} has a lot of arguments. This can be a bit daunting, even for those who are familiar with {ggplot2}! We will walk you through how to modify some aspects of a {ggplot2} theme and give you the confidence to try making your own theme modifications.
Published: June 23, 2022
Choosing which colours to use in a plot is an important design decision. This blog post will show you how to make a custom colour palette that is compatible with {ggplot2}.
Published: September 20, 2018
Last week I spent some time reminiscing about my PhD and looking through some old R code. This trip down memory lane led to some of my old R scripts that amazingly still run. My R scripts were fairly simple and just created a few graphs.
Published: September 2, 2018
Ever wonder what an evolving gif of each premier league team’s goal difference vs points would look like made in R? Look no further! Most of this is going to be setting up the data (as always) instead of actually plotting the data.
Published: August 21, 2018
In our previous post, we demonstrated that contrary to popular opinion, it is possible to generate attractive looking plots using just base graphics. Although we did confess, that it did take a lot of time and effort. In this post, we repeat the same exercise.
Published: February 1, 2018
Hi all, so given our logo here at Jumping Rivers is a set of lines designed to look like a Gaussian Process, we thought it would be a neat idea to recreate this image in R. To do so we’re going to need a couple packages. We do the usual install.packages() dance (remember this step can be performed in parallel).
Published: November 27, 2017
The {plotly} package. A godsend for interactive documents, dashboard and presentations. For such documents, there is no doubt that anyone would prefer a plot created in {plotly} rather than {ggplot2}. Why? Using {plotly} gives you neat and crucially interactive options at the top, whereas {ggplot2} objects are static.
