NHS-R Workshop: Level up your plots! - 04/11/22
Channel: NHS-R Community
Date: 2022-11-08

Level up your plots: tips and tricks for creating compelling data visualisations in R
Friday 4th November 202
Led by Cara Thompson, Freelance Data Consultant - Building Stories with Data

Pre-requisites: 
It would be helpful for participants to have a basic grasp of:
- creating a plot with ggplot2
- data wrangling within the tidyverse

About the course:
“Ooh, nice ggplot!” is never the reaction we’re after when we’ve spent time putting together a plot in R.

Instead, we want the plot to help readers engage well with the key patterns in the data.

This workshop will give delegates a tour of the ways we can use ggplot to create compelling publication-ready data visualisations.

We will code our way from a basic plot to a plot which presents a clear story in an aesthetically pleasing way, and delegates will be encouraged to apply the tips and tricks we explore together to their own plots.

During the workshop, we will cover:
- a quick overview of foundational ggplot concepts
- design principles we can apply to our datavisualisations
- how to choose and apply a bespoke colour scheme, both to the text and to the data in the plot
- how to change the fonts and colours of text
- how to create polished annotations to support the main story of the plot
-how to export high quality plots for publication
- sources of dataviz inspiration for future projects
These tips will be applicable to a wide range of plot types, to maximise relevance to delegates working with different types of data. They will be encouraged to ask questions and apply these tips to their own plots during the workshop, with the aim of equipping them with the design and coding know-how to create compelling datavisualisations with their own data.

Learning objectives
By the end of the workshop, delegates will be able to:
- describe basic design principles that they can apply to datavisualisations
- describe the basic components of a ggplot plot
- apply a colour scheme they crafted themselves to their own plots
- write code which modifies the different default ggplot elements
- work with fonts, colours and alignments to make the text of their plot an integral part of the visualisation
- export publication-ready plots