R Data Science Skill

R-first data science workflows emphasizing tidyverse idioms, functional programming, and reproducible research.

Core Principles

1. Tidyverse-first: Prefer tidyverse solutions; use data.table or base R when performance requires
2. Pipelines over scripts: Use |> (native pipe) for clarity; %>% acceptable in existing codebases
3. Functional style: Leverage purrr for iteration; avoid explicit loops
4. Lazy evaluation: Use DuckDB/dbplyr to push computation to the database
5. Reproducibility: Structure projects with targets for pipeline orchestration

Quick Reference

Data Import/Export

# CSV (readr - tidyverse)
df <- read_csv("data.csv", col_types = cols())