The R ecosystem spans base R, recommended packages on CRAN, Bioconductor for genomics, and tools like RStudio, renv, and pak. Understanding how pieces connect helps you choose playground vs local setup.
Key pieces
- Base R — vectors, data frames,
lm(),plot()—no install needed - CRAN — community packages via
install.packages() - Tidyverse — dplyr, ggplot2, tidyr, readr (local install; taught in prose here)
- R Markdown — knit reports to HTML/PDF locally
Analysis path in this curriculum
This track covers R language fundamentals. Join results from SQL exports, visualize, model, and document—then explore Data Science for cross-tool workflows.
Important interview questions and answers
- Q: Base R vs CRAN package?
A: Base R ships with the interpreter; CRAN packages extend functionality and install on demand. - Q: What is the tidyverse?
A: A curated set of packages (dplyr, ggplot2, etc.) sharing consistent data-frame idioms—install locally, not in this playground.
Self-check
- What function installs CRAN packages?
- Which package family handles grammar-of-graphics plotting?
Tip: Base R ships with the interpreter; tidyverse and R Markdown install locally via install.packages().
Interview prep
- What is CRAN?
Comprehensive R Archive Network—the primary repository for R packages.
- What is tidyverse?
A meta-package collection (dplyr, ggplot2, etc.) sharing consistent data-frame idioms—install locally.