Elegant R: Tips from a Software Developer
summary
Shows concrete edits and tools that make R code maintainable: using RStudio projects to fix working directories, extracting repeated code into small functions, and removing intermediate variables with the magrittr pipe. Demonstrates dplyr/tidyverse verbs, DBI + RPostgres with Docker-loaded Northwind and dbplyr lazy SQL translation that generates queries, reticulate for Python interop, building a tiny package and sharing via install_github, plus RStudio snippets and addins like styler and data paste that actually speed workflows.
AI-written summary · about
chapters (15)
- 0:00Introduction to talk
- 1:35Using R projects for organization
- 4:32Organizing code with functions
- 7:30Cleaning up repetitive code
- 10:44Handling messy data with pipes
- 14:04Grouping and summarizing data
- 18:48Connecting R to databases
- 27:43Integrating Python with reticulate
- 30:19Refactoring subsetting code
- 32:11Creating reusable R packages
- 34:43Using RStudio snippets
- 36:09Exploring RStudio add-ins
- 38:15Enhancing R Markdown documents
- 44:26Useful R packages overview
- 45:49Q&A and closing
related talks
51mProgramming in the Tidyverse
18mInteractivity and Programming in the Tidyverse
21mA guide to modern reproducible data science with R
24mHow to Write Reproducible Manuscripts
29mGrammars of Data: lessons from ~20 years of the tidyverse
15mAdvocating for Automation: Adapting Current Tools in Environmental Science with R
18mtidymodels: Adventures in Rewriting a Modeling Pipeline
20m15 Years of R in Quantitative Finance