
R is a programming language for statistical computing and data visualization. It has been widely adopted in the fields of data mining, bioinformatics, data analysis, and data science. Wikipedia
Created Year: 1993Created by: Robert Gentleman • Ross Ihaka
Designed by: Robert Gentleman • Ross Ihaka
Operating systems: BSD • GNU/Linux • Microsoft Windows • Unix-like operating system • macOS
Implemented in: C • Fortran • R
Aliases: GNU R, GNU S, R language, R programming language
Wikidata: Q206904
Influenced: Julia
Influenced by: Common Lisp • S • Scheme
Programming paradigms: array programming • functional programming • imperative programming • object-oriented programming • procedural programming • reflective programming
Language types: multi-paradigm programming language
R Influence Network
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Hello World in R
cat("Hello World")
Source: github.com/leachim6/hello-world
Free R books, articles, documentation
- Advanced R Programming - Hadley Wickham
- An Introduction to ggplot2 - Ozancan Ozdemir
- An Introduction to R - David M. Smith, William N. Venables
- An Introduction to Statistical Learning with Applications in R - Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani (PDF)
- Behavior Analysis with Machine Learning Using R - Enrique Garcia Ceja (HTML) (CC BY-NC-ND)
- Beyond Multiple Linear Regression - Paul Roback, Julie Legler
- blogdown: Creating Websites with R Markdown - Yihui Xie, Amber Thomas, Alison Presmanes Hill
- Cookbook for R - Winston Chang
- Data Analysis and Prediction Algorithms with R - Rafael A. Irizarry
- Data Mining Algorithms In R - Wikibooks
- Data Visualization with R - Martin Schweinberger (HTML)
- Efficient R programming - Colin Gillespie, Robin Lovelace
- Exploratory Data Analysis with R - Roger D. Peng
- Forecasting: Principles and Practice - Rob J Hyndman, George Athanasopoulos
- Functional Programming - Sara Altman, Bill Behrman, Hadley Wickham
- Geocomputation with R - Robin Lovelace, Jakub Nowosad, Jannes Muenchow
- Introduction to Probability and Statistics Using R - G. Jay Kerns (PDF)
- Learning Statistics with R - Danielle Navarro
- Mastering Software Development in R - Roger D. Peng, Sean Kross, and Brooke Anderson
- Model Estimation by Example, Demonstrations with R - Michael Clark
- Modern R with the tidyverse - Bruno Rodrigues
- Modern Statistics with R - Måns Thulin
- ModernDive - Chester Ismay, Albert Y. Kim
- Practical Regression and Anova using R - Julian J. Faraway (PDF)
- R for Data Science - Hadley Wickham, Mine Çetinkaya-Rundel, Garrett Grolemund
- R for Spatial Analysis (PDF)
- R Language for Programmers - John D. Cook
- R Notes for Professionals - Compiled from StackOverflow Documentation (PDF)
- R Packages - Hadley Wickham, Jenny Bryan
- R Practicals (PDF)
- R Programming - Wikibooks
- R Programming for Data Science - Roger D. Peng
- R Succinctly, Syncfusion (PDF, Kindle) (email address requested, not required)
- Statistical Inference via Data Science - Chester Ismay, Albert Y. Kim
- Summary and Analysis of Extension Program Evaluation in R - Salvatore S. Mangiafico
- Supervised Machine Learning for Text Analysis in R - Emil Hvitfeldt, Julia Silge
- The caret Package - Max Kuhn
- The R Inferno - Patrick Burns (PDF)
- The R Language
- The R Manuals
- Tidy Modelling with R - Max Kuhn and Julia Silge
- Tidy Text Mining with R - Julia Silge, David Robinson
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Latest data update: 2025-08-16