Data visualization and R
Data visualization is one of the key steps of any data science related process. There are hundreds of possibilities available when it comes to visualizing data, and choosing and using the right one are determining factors in accurately getting your message across. R programming language is one of the most common tools used for this process.
R is fabulous for creating charts. It allows you to create all types of visualizations and lots of libraries are developed to help users scan them quicker. However, it can sometimes be challenging – and extremely frustrating – to look for the right code to compute a desired plot.
The R Graph Gallery by its creator, Yan Holtz
The R graph gallery is a collection of R graph examples, organized by chart type, searchable by R function, and with reproducible codes and explanations.
The R graph gallery presents hundreds of dataviz possibilities
This gallery is a collection of over 300 R graphics. The website displays them with explanations and reproducible codes allowing all users to rapidly understand the code and apply it to their own dataset. To facilitate research, charts are classified by type (such as boxplot, scatterplot, map or histogram) and the search bar will help you to find specific R functions.
The R graph gallery home page
Browsing the All graph page is also a good way to find some inspiration for new ways to visualize your data: why not try stream graphs, radar charts or circular plots? If you are already familiar with the basic functions of R, check out the interactive charts section that contains examples of some of the html widgets. Interactive graphics are highly accessible with R and can greatly improve your dataviz skills. Another plus is the complete section dedicated to the popular ggplot2 library!
Last but not least, the gallery proposes several useful examples for “omic people”. R is widely used by biologists and there are a lot of packages out there that have been developed for omic data analysis. Suppose for example that you need to draw a Manhattan plot to show the relationship between SNPs and a phenotype – try the qqman library and the graph #101 that will show you how to use it!
The R graph gallery is new and growing rapidly, notably thanks to the numerous contributors (whom I warmly thank). Please feel free to contact me if you have any suggestions to improve this project or if you detect any malfunctioning. And of course, any new R charts are more than welcome!