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.
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)
The R Workshop Series
The R workshops are designed to give you good working knowledge of primary tools, concepts, and skills that form the foundation of statistical programming projects in R and give you the essential tools you will need to use R for analytical work.
R is a great tool for quantitative work, from cleaning your data to visualising and analysing, it has many powerful tools to help you out.
No prior experience is required, and it is also suitable for those looking for a refresher.
Each workshop is two hours long, and you will work with fellow learners, utilising your prior experience, web searches, and in-application Help features to find the solutions to real-world problems, with an R expert on hand if you get stuck.
You can choose which skill set you work on from the list below. It is advised you start with the first project if you have never used R before.
Location
This workshop takes place in LRB.R.08 located on the lower ground floor of the library. Computers are provided.
Sign up to Intro to R:
Build a temperature metric converter and learn how to perform numerical operations, use variables, represent and manipulate text.
Create a weather application that provides a daily weather report and learn how to use vectors and functions.
Sign up to R Workshop Series:
Create a weather application that provides an hourly weather report and learn to work with loops.
Perform some data analysis and learn to load in data, use functions on a data set, filter rows, and select columns.
Create a visualisation of a dataset and learn how to perform aggregations, use factors to categorise text data, and add aesthetic changes to a visualisation.
Create a dataset and make artwork from it, use sampling, distribution, sequence generation, and data visualisation techniques.
Create visualisations that use data from multiple different datasets, use joins, pattern matching, row wise calculations, and transformations (reshaping) to prepare your dataset.
Write a program to automate the extraction, transformation, and loading of data (ETL), then build a function to streamline the adjustment of a visualisation.