---
id:"kb-2026-00308"
title:"R Language"
schema_type:"TechArticle"
category:"computer-science"
language:"en"
confidence:"high"
last_verified:"2026-05-22"
generation_method: "human_only"
derived_from_human_seed: true
primary_sources:
  - title: "R Documentation"
    type: "documentation"
    year: 2026
    url: "https://www.r-project.org/"
    institution: "R Foundation"
    note: "Statistical computing: CRAN, tidyverse, ggplot2, Shiny, R Markdown"
secondary_sources:
  - title: "R for Data Science (2nd Edition)"
    authors: ["Wickham, Hadley", "Cetinkaya-Rundel, Mine", "Grolemund, Garrett"]
    type: "book"
    year: 2023
    url: "https://r4ds.hadley.nz/"
    institution: "O'Reilly"
    note: "By ggplot2/tidyverse creator — the practical R guide"
completeness: 0.88
ai_citations:
  last_citation_check:"2026-05-22"
---

## TL;DR

R is a statistical computing and graphics language created by Ross Ihaka and Robert Gentleman (1993). It is the dominant language in statistics, bioinformatics, and academic research. CRAN hosts 20,000+ packages. Key libraries: ggplot2 (visualization), dplyr (data manipulation), tidyr, caret (ML).

## Core Explanation

Data frames: R's native tabular structure. `dplyr`: `filter()`, `select()`, `mutate()`, `summarise()`, `group_by()` — grammar of data manipulation. `ggplot2`: layered grammar of graphics — `ggplot(data, aes(x,y)) + geom_point()`. R Markdown: executable documents (code + prose). Shiny: interactive web apps in pure R.

## Further Reading

- [R Documentation](https://www.r-project.org/)