This course introduces some relatively new additions to the R programming language: dplyr and ggplot2. In combination these R packages provide a powerful toolkit to make the process of manipulating and visualising data easy and intuitive.
Mark Dunning, CRUK
Thomas Carroll, Imperial College London
Audience and Prerequisites
- Existing R users who are not familiar with dplyr and ggplot2
- Those with programming experience in other languages that want to know what R can offer them
- Attending the Introduction to Solving Biological Problems using R course would be beneficial, but not essential. We will assume that you know how to load RStudio, create variables and use functions. Some good introductory videos can be found here.
- Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals.
Syllabus, Tools and Resources
During this course you will learn about:
- How R enables reproducible research
- What constitues a tidy dataset
- "Piping" commands together to form a workflow
- Subseting and filtering datasets using dplyr
- Producing summary statistics from a dataset
- Joining datasets using dplyr
- The grammar of graphics approach to plotting used in ggplot2
After this course you should be able to:
- Create reproducible documents
- Import and tidy and datasets into R
- Use dplyr to explore a dataset interactively
- Produce simple analysis workflows in R
- Make publication-ready graphics using ggplot2