Syllabus - Data Visualization for Economics Research
Lyon Summer School in Empirical Research Methods - ENS de Lyon
Instructor
Course objectives and overview
A significant portion of communicating economic research results-whether in presentations or written papers—relies on graphs and visuals. This session aims to help you develop essential skills for effective data visualization. We will cover fundamental visualization principles and general best practices before examining the specific challenges of data visualization for causal inference. While it can be a powerful rhetorical tool for causal inference, data visualizations can also be misleading if not handled carefully.
Class outline
- Introduction
- Usefulness and importance
- Key data viz principles
- Building a graph
- Data viz for research in economics
- Main take-away points
Useful handbooks
Data Viz
Here is a short list of useful applied data visualization handbooks:
- Fundamentals of Data Visualization provides a great code-free introduction to data viz.1
- Modern Data Visualization with R and Data Visualization - A practical introduction both discuss key data viz concepts and teaches you how to apply them in R and ggplot.
- R for Data Science provides a nice introduction to ggplot, THE package to build plots in R. To go further you can read this book.
Resources for implementation (in R)
R is a super useful tools for applied economics analysis (and way beyond that). Thanks to the ggplot package, it is also one of the best tools out there to make graphs in this field. If you do not know R, I would only encourage you to learn and use it. To do so, here is a list of useful resources:
- R for Data Science: definitely the best resource to learn R and the tidyverse by yourself.
- R cheatsheets: great summaries of the functions in key tidyverse packages.
- The tidyverse style guide: a very short book to help you write more legible R code.
- Tidy design principles a more advanced book to help you write better R code.
Footnotes
Although R code can be found on the book’s GitHub if needed.↩︎