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UNSWCodeRs_Data_visualisation_workshop

This repository is for the development and eventual release of code for a data visualisation workshop. Authors: C E Page & F Robinson

Contact: c.page@unsw.edu.au, fiona email

Data Visualisation using R: Applying principles of graphic design to making figures

In this workshop we aim to give you a taste of what can be possible in R. We will dazzle you with an introduction to graphics creation using ggplot(), before we then change how you see data through presentation of some core graphical principles (CRAP - Contrast, Repitition and Alignment). Through applying CRAP you'll find out how we can look to better visualise data through creating, and grouping plots that present results and findings in clear and effective ways, better communicating the work you do! We will then present a worked example, where we evolve a plot from basic visualisation, to a publication ready rain cloud plot.

This course assumes you have some basic coding skills in R. We provide an overview of ggplot() and provide code for all worked examples.

This workshop has been developed based on a number of freely available online tutorials and blogs. Without these as guides and inspiration for material and code this workshop might have been a little more boring and would be far from as informative (we hope!). We have referenced links throughout this tutorial in relevant sections, and provide a full list of these below. We encourage you to use this workshop as guide to help inform how you create visualisations - but the real magic happens when you develop your own a check out these great resources.

Workshop material

All of the data and scripts you need for todays workshop can be found in this repository. To run through the code yourself we recommend downloading a zip file of this gitrepo.

Scripts

This workshop is split into two sections that correspond to the below scripts:

    • Part 1: giving a CRAP with ggplot() (without all code)
    • FULL Part 1: giving a CRAP with ggplot() (with all code)
  1. Part 2: from basic plot to publication ready, evolving a ggplot()