Module 2 - Data Vizualization and Basic Transformations
Overview and Deliverables
This module focuses on visualization, which is not only one of the first tools that you should use when faced with a new dataset but also the primary way that we communicate quantitative information with other people. We will discuss principles of good visualizations and how to use the ggplot2 package for combinations of numerical and categorical data. ggplot2 is based on a conceptual framework called the “grammar of graphics”, which you will become familiar with as we build plots. Your first homework assignment, Lab 1, will be due at the end of this week. Your reading will also cover some of the basics of using R which might be a review if you already are an experienced user. Here are your deliverables:
- 9/1: Attend the class meetup (remember to submit the meetup reflection)
- 9/7: Submit Lab 1 on the Brightspace page for the course
Learning Objectives
- Data Visualization for Numerical and Categorical Variables with
ggplot2 - Learn principles of good visualizations
- tidyverse code conventions
- Basic Data Transofrmations with
dplyr
Readings
The basics of using the tidyverse:
- RDS (R for Data Science): Chapters 1-4
Two good articles on making honest visualizations and identifying dishonest ones:
Additional Resources:
- Fundamentals of Data Visualization. Claus O. Wilkey. (2019). O’Reilly.
This is my favorite modern book on data visualization, and it also uses ggplot2 as the primary tool. If you are uncertain about what visualizations might be appropriate for a given problem, this is a good place to check for inspiration. The intended audience is scientists but it is equally relevant for people working in other industries. Chapters 1-5 and Chapter 29 would be good additional readings if you wanted to go a little more in depth.
- Data Visualization: A Practical Introduction. Kieran Healey.
Well written book on R and data visualization. This is a good place to turn if you are struggling with the style of the main course textbook.
- A Layered Grammar of Graphics. Hadley Wickham. Journal of computational and graphical statistics 19.1 (2010): 3-28.
This paper explains the concepts and thinking behind ggplot2.
- ggplot2 website. This is another excellent source of resources and information on ggplot2