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R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics, and data analysis. The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.
R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues.
Learn how to code and clean and manipulate data for analysis and visualization with the R programming language.
An introduction to R. This page discusses R installation, RStudio, operators, data types, creating variables, importing data, functions, and installing packages.
The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code.
a well developed, simple and effective programming language (called ‘S’) which includes conditionals, loops, user defined recursive functions and input and output facilities. (Indeed most of the system supplied functions are themselves written in the S language.)
R programming is an interpreted programming language widely used to analyze statistical information and a graphical representation. R programming is popular in the field of data science among data analysts, researchers, statisticians, etc.
