As a self-taught R user, I am deeply indebted to the R community for making code samples and interesting datasets publicly available. In order to pay it forward, I use this page to (1) provide the data/code behind my content.1 and (2) list some incredible resources (for data science, R, and economics) that I frequently use.

I hope all the below helps you to build/write/create stuff! Remember that with coding, practice makes perf… better.

via XKCD

(1) Resources from me to you

Projects on my blog

In general, my project materials are available as github repos. I also publish R notebooks as RPubs. I link to relevant repos/notebooks at the bottom of all blog posts.

(While my Github repos will include the .Rmd files for R notebooks, I also share notebooks as published through RPubs since they are easier to read in that format. Example: here is a Rmd file on Github, here is the same notebook on RPubs.)

Data visualizations/explorations

Theory diagramming

Website and CV examples

(2) Resources from others to you

Finding data

Data visualization inspo

R resources

Using R broadly:

Online community links:

R for data visualization:

Using R for projects:2

Using xaringan for slides:

Making a website with blogdown:

Making a CV:

Predictive Modeling with Tidymodels:

Empirical Economics Resources

Causal inference concepts:

Lecture notes and textbooks on causal inference/metrics:

Visualizations particularly useful to empirical research:

Staggered differences-in-differences resources:

Misc. Resources

Coding as a stats-y person with stats-y software:

Using version control:

On Economics RA-ing, PhD-ing, etc.:

  1. Please don’t judge 2015-me too much.
  2. Not R but here’s a great Stata Coding Guide from Julian Reif
  3. Highly rec seminar tips #1, 3, 4, 6