IMPRS course 'Data visualisation with R'

1.  General information

Date: 22-23 February, 2023
Time: 9.00 AM - 4 PM
Place: MPI for Biogeochemistry
Lecturer: Guido Schulz
Category: Transferable skills
Credit points: 0.4

2.  Course description

In this two day course, participants will learn how to create their own data visualizations using the statistical software R while following common best practices of data visualization. The course starts off with some theory on what makes a good data visualization and what pitfalls should be avoided. Then, we will dive into the grammar of graphics and its corresponding R package “ggplot2”. We’ll spend quite some time working on exercises using “ggplot2” and extend our plots with new features step by step - slowly approaching real life applications. We’ll also cover approaches for interactive visualizations and learn how to make basic static as well as interactive maps in R.

3.  Learning Goals

At the end of the course participants will be able to

• take well informed decisions on how to visualize their data,
• create basic, reproducible, insightful visualizations using R and
• efficiently search online for solutions to their specific visualization problems.

4. Syllabus

• Visualization theory - the what and the why
• Common pitfalls and best practices in data visualization
• Visual vocabulary - how to pick the right viz
• The grammar of graphics in R: ggplot2 (theory, practice, exercise)
• Extending ggplot2 (theming, labeling, highlighting, exercise)
• Interactive Visualizations (plotly, exercise)
• Maps in R (Short Intro to sf, static maps, interactive maps, exercise)

Depending on how much time there is left, additional topics could potentially be introduced:

• Specifics of visualizing time series, uncertainty or significance
• Interactive visualizations with shiny
• Visualizations in dynamic reports
• Animations with gganimate

5. Prerequisites

• Basic knowledge of R and RStudio IDE
• Participants bring their own laptop with a working, recent installation of R and RStudio IDE. Participants will complete the exercises on their own laptops.
  
• Installation of various visualization related R packages (about a week before the course an R script that installs the necessary R packages will be sent to participants)

If you have any questions in advance, don’t hesitate to contact the tutor of the course Guido Schulz (guido.schulz@inwt-statistics.de).

6.  Registration

The registration is possible via this webpage.