This document is meant to inform academics, students, and anybody learning to code, especially in R using RStudio, the specific measures that can be taken to make code more readable. High readability of code is likely to lead to higher reliability of results, higher reproducibility, higher efficiency of coding and higher reusability among other things. Readability and quality control of code is largely neglected in science and academia and often even seen as unnecessary. However, having worked in the software industry in a company known to follow rigorous quality standards, I understand its importance. These are practices that I have adapted into coding with R in my own scientific work and highly recommend to others.
These slides were prepared for live presentations but I have tried to make them self-explanatory to also be usable independently. Some version of these slides have been presented so far in:
- R Ladies, Nijmegen, the Netherlands on June 11th 2020
- Open Science Community, Nijmegen, the Netherlands on October 28th 2020
- R Ladies, Coventry, the UK on December 4th 2020
- R Ladies Bergen, Norway on March 22nd, 2021
- Key Practices for the Language Scientist, International Max Planck Research School on April 1st, 2021
- Key Practices for the Language Scientist, International Max Planck Research School, 2022
- Key Practices for the Language Scientist, International Max Planck Research School on January 23rd, 2023
The current version of the presentation uploaded here is closest to that presented in R Ladies Coventry on December 4th 2020. However, it will probably be updated from time to time with future iterations.
230222 Best Practice for Programming in RIf you would like me to give a talk or conduct a workshop on this topic, feel free to contact me using the Contact page.