Project

1 Objectives

  • Test your data wrangling and visualisation skills.

2 Start a Script

For this lab or project, begin by:

  • Starting a new R script
  • Create a good header section and table of contents
  • Save the script file with an informative name
  • set your working directory

Aim to make the script a future reference for doing things in R!

3 Introduction

This particular lab is a little different to the others as it introduces your mini-project for the week. One of the best ways to hone your data visualisation skills is to practice. Then practice some more! There are a huge number of resources available to help you practice creating data visualisations, but the most popular with R users is Tidy Tuesday.

3.1 Tidy Tuesday

A weekly data project aimed at the R ecosystem. Every week a raw dataset is posted to GitHub, along with a related chart or article, and people are invited to explore the data. This exploration usually takes the form of some type of data visualisation. Datasets are usually “tamed” but not always tidy, which provides an useful opportunity to practice your data wrangling skills alongside your visualisation skills. Although this project is largely based on the tidyverse ecosystem of packages there are no formal restrictions and any code-based methodology is encouraged.

4 Mini-project

You are tasked with producing a data visualisation based on a Tidy Tuesday dataset. Your visualisation must have a clear narrative for the data and not simply be descriptive - tell me a story. You are free to use any R-based approach to complete the mini-project. I expect to see a GitHub repository containing a fully reproducible R Markdown document detailing:

  • A brief introduction to the data;
  • Data cleaning code;
  • Exploratory data analysis code;
  • Final visualisation code.

You may select your own dataset from the Tidy Tuesday archive here. Please let the module leader know which one you have chosen to ensure that everyone has their own unique dataset.

This mini-project is no small feat, so to ensure you have sufficient time to complete it during the week I have allocated all of Thursday afternoon for you to work on it. We will finish the module off with you presenting your data visualisation to the group during Friday’s live afternoon session. If you want some Tidy Tuesday inspiration, check out the Twitter Hashtag or the following screencasts: