What is R?

R is an open-source, widely used statistical programming language, that is easy to learn and, thanks to its many extensions, can be used as a general-purpose programming language. R was first released in 1993 and has since risen greatly in popularity, being used in academic institutions as well as companies such as the BBC, NHS, Google, Facebook, Twitter, Microsoft, Wellcome, Sanger Institute, New York Times and Mozilla. 

R is simple to use and easy to read, this makes sharing your code easier and enables you to write your code faster. This is taken further by the Tidyverse ecosystem within R, that provides even easier to read code as well as excellent documentation. R is one of the best choices for data science and machine learning due to its wide pool of libraries for statistics, data manipulation and wrangling, data visualisation, and modelling; it is used across many sectors such as finance, healthcare, technology and retail for these purposes. R is the gold standard choice for data visualisation in data science thanks to the ggplot2 library and its many extensions. R also has one of the best open-source Integrated Development Environments (IDE) available in RStudio, not only does it make programming in R easy, it makes it simple to create documents with your code and outputs in various output formats such as HTML, Word, Powerpoint, and PDF.   


The R Workshop Series

The DSL R workshops have an open format, which are split into two workshop series.

The Fundamentals series takes you from getting started in R, key data types, using logic, and loading datasets; you’ll be doing some basic data cleaning and analysis along the way.

The R Data Wrangling and Visualisation series introduces popular R data science libraries, allowing you to do complex data manipulations, perform summary statistics, and make a wide array of data visualisations.

 All workshops will be held in-person and are for two hours per session.


This workshop takes place in LBR.R.08 located on the lower ground floor of the library. Computers are provided. 

Technical Requirements 

All software is provided on lab computers. If you would like to use your own laptop you will need install the following software: 

R ( Mac / Windows

RStudio Desktop (Mac/Windows - you must install R first to use RStudio) 

XQuartz (install if using Mac with operating system greater than 10.5) 


We have also curated some self-study courses that can be accessed via our Moodle page.  If you can't find what you're looking for below, please email digital.skills.lab@lse.ac.uk or attend one of our drop-in sessions for advice. 

We also have workshops and self-study courses for Python

General guidance to using the open sessions:

Book onto an open session for the R series you are working on. This will be either Fundamentals or Data Wrangling and Visualisation. You are advised to start with the R Fundamentals series and with R Fundamentals 1 – Introduction to R unless you already have experience using R

Keep booking onto open sessions to complete whatever R workshop is next in the series for you. You will likely complete one and a half or two workshops per session

Use our workshop flow graphic for guidance. 

Here are some example scenarios to help you know where to start and how progression works:

  • Scenario 1: You have completed R Fundamentals 1 and 2 -> come to an open Fundamentals session and start with R Fundamentals 3
  • Scenario 2: You have completed R Fundamentals 1 through to 6 -> come to an open Fundamentals session and start with R Fundamentals 7, if you finish start with R Data Wrangling 1 (from the Data Wrangling and Visualisation series)
  • Scenario 3: You have used R before and feel a bit comfortable but might want a refresher -> come to an open session of either Fundamentals or Data Wrangling and Visualisation and pick a workshop where you think you want to get a refresher. You might need a review of using conditional logic in R then come to the Fundamentals series and R Fundamentals 6. You might want a refresher on joining datasets, then you will want to come to the Data Wrangling and Visualisation series and R Data Wrangling 3.

Click on the link below to check availability and book your place: