Data Visualisation with R - Online

Data visualisation is one of the most important steps in any analysis journey. Visualisations allow us to explore our data, identify errors and outliers, generate hypotheses about possible relationships between variables, and communicate results clearly and efficiently. ggplot2 is a powerful R package that was designed to create publication-quality graphics in seconds. The joy of ggplot2 is its flexibility: graphs are built in layers which can be easily customised, ensuring novel plots to fit almost any situation.

This online course will introduce the ggplot2 package and its underlying grammar of graphics. Participants will understand how to choose the most appropriate type of visualisation, based on the type and number of variables, and the intention of the plot. We will then build visualisations, layer by customisable layer, to transform simple plots into beautiful, informative graphics.

 The course covers:

• How to load, tidy, and prepare data for visualisation
• Introduction to ggplot2: how to produce a simple graph
• Enhance visualisations by customising layers: scales, themes, and annotations
• Faceting: multiple visualisations in one place
• Creating personalised colour palettes and themes for consistent visualisations

 By the end of the course participants will:

• Create compelling, clear data visualisations using the ggplot2 package
• Be able to customise graphs using scale and theme functions
• Know how to add annotations to graphs to make them as clear as possible
• Know when to facet graphs to show multiple plots on the same graph
• Save personalised colour palettes and theme functions to ensure visualisations are consistent

This course is open to anyone that would like to level up their data visualisation using the ggplot2 package. This could include PhD students, academics, government or other public sector analysts, etc. from any discipline.  Participants are expected to have some experience of loading and tidying data in RStudio using Tidyverse packages.

Participants will need R and RStudio installed on their computer. They will need to check that they are able to install packages from the online R repository (this is usually not an issue but some departments with secure data may have issues if they require an administrator password to install things to their machine). For this, participants can run the following code which will install and load the package we are using to their computer:

install.packages("tidyverse")

library(tidyverse)

This course will run from 10am to 4pm on Wednesday 27 November 2024