Website: I wrote my website using blogdown and host it using netlify. I have previously used both Jekyll and Hugo hosted on github pages, but overall find the blogdown + netlify combination to be much more straightforward. I wrote a blog post on how I made my website a while ago.
D3.js: By far the best resource I’ve found for learning D3 is Scott Murray’s Interactive Data Visualization for the Web: An Introduction to Designing with D3.
- Causal Inference: When I started learning about causal inference, I found most of the papers totally unintelligible. The best resource I found for learning the basics of causal inference was Imbens and Rubin’s Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction, which was surprisingly accessible.
Colours: My favourite way to choose colors for a plot is a website called https://coolors.co/, which randomly generates appealing color palettes for you to choose from. Just hit the space bar to generate a new palette!
Data viz best practices: I absolutely loved Cole Nussbaumer Knaflic’s Storytelling with Data: A Data Visualization Guide for Business Professionals. I totally bought it on a whim a couple of years ago, and learnt a huge amount. This book made me a lot more thoughtful about the visualizations that I produce.
Tidyverse: The resource that I usually point people towards for learning the tidyverse is Garrett Grolemund and Hadley Wickham’s R for Data Science.
R packages: When I made my first R package, Hadley Wickham’s book on R packages was indispensable!
Presentation and communication