References

• R for data science: https://r4ds.had.co.nz/

• Row oriented workflows: https://github.com/jennybc/row-oriented-workflows#readme

• What they forgot to teach you: https://whattheyforgot.org/

• Advanced R: http://adv-r.had.co.nz/

• Tidy evaluation: https://tidyeval.tidyverse.org/

• R packages: http://r-pkgs.had.co.nz/

• roxygen2: https://roxygen2.r-lib.org/

• How R searches and finds stuff: http://blog.obeautifulcode.com/R/How-R-Searches-And-Finds-Stuff/

• Parallel processing with a purrr-like interface: https://davisvaughan.github.io/furrr/

• Recursive lists to use in teaching and examples: https://github.com/jennybc/repurrrsive

• Tidyverse principles: https://principles.tidyverse.org/

Grolemund, Garrett, and Hadley Wickham. 2017. R for Data Science. O’REILLY.