Correspondence Analysis visualization using ggplot

Correspondence Analysis visualization using ggplot

What we want to do Recently, I used a correspondence analysis from the ca package in a paper. All of the figures in the paper were done with ggplot. So, I wanted the visualization for the correspondence analysis to match the style of the other figures. The standard plot method however, produces base graphics plots. So, I had to create the ggplot visualization myself. Actually, I don’t know if there are any packages that take a ca object (created by the ca package) and produce ggplots from it.

How to save (and load) datasets in R: An overview

What I will show you In this post, I want to show you a few ways how you can save your datasets in R. Maybe, this seems like a dumb question to you. But after giving quite a few R courses mainly - but not only - for R beginners, I came to acknowledge that the answer to this question is not obvious and the different possibilites can be confusing.

Using custom scales with the ‚scales‘ package

Maybe you already heard of the package “scales” - and if you didn’t hear about it, you might have used it without knowing (e.g., in the context of ggplot2 graphs). I want to show you a few of the functionalities of the “scales” package. I will also show you how to create your own scales. There are several possible reasons why you might want to use these: Automatically create axis labels that show percentages (0.

How I started a blog based on blogdown: A walkthrough

After a long time of running my blog on, I finally wanted to move it to a solution that’s better suited for the kind of contents I am posting. Namely, that’s content related to R and everything you can do with it - from analyzing large datasets to technical details or benchmarking stuff. For me, it sounds really logical to blog about R with R (with the help of RStudio).