Resources for learning R

This course assumes participants already have some programming experience with R, assuming familiarity with things like: creating and setting variables, the basic data structures (dataframes, vectors, lists), using functions and running R code and viewing console output. You can refresh your memory of these concepts by consulting Introduction to R.

Installing and using packages

Participants will need to install some extra packages for this course. In general, this can be done by using the install.packages function in R. For example, to install the dplyr package, run the following within an R session:

install.packages("dplyr")

To then use this package in your own code (or in the R console), you have two options:

1. Include the line library(dplyr) in your code to import all the functions (and any other objects e.g. example dataframes) from the package for you to use. For example, this would allow you to use the mutate function from dplyr.

2. Use ‘namespace’ notation to access a specific function / object from within the package. For example, to use the mutate function from dplyr without importing the whole package, we can write dplyr::mutate. Note that you don’t need to run library(dplyr) for this to work.

Further resources for learning the Tidyverse

This course will give you a grounding in using the Tidyverse collection of packages in R to work with data. You may wish to look at the following supplementary materials after the course:

• Cheatsheets for several Tidyverse packages, including the ones we’ve covered in this course, are available at https://posit.co/resources/cheatsheets/. These are a great way to quickly look up function(s) that help you perform some concrete task. Often it’s a good idea to look at the cheatsheet to know what functions(s) you need, then use the help system in R to read the documentation, or search the web for further advice.

• The R for Data Science book (2nd ed.) by Hadley Wickham, Mine Çetinkaya-Rundel and Garrett Grolemund is a freely available, online book which covers lots of aspects of working with and visualising data using the Tidyverse in a way that’s approachable for non-expert R programmers.