IMPRS course 'Data visualisation with R'
- Start: Feb 22, 2023
- End: Feb 23, 2023
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.
- 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
- Basic knowledge of R and RStudio IDE
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 (email@example.com).
The registration is possible via this webpage.