Also known as: R
R is a dynamic, interpreted language specialised for statistics, data analysis, and plotting.1 It is beloved by statisticians and researchers, and is excellent for analysis and visualisation but less suited to general-purpose programming.
Overview
R grew out of the academic statistics community and remains organised around that work.2 Its data frames, vectorised operations, and enormous library of statistical methods make it a natural fit for exploratory analysis, modelling, and producing charts. Packages distributed through CRAN cover an extraordinary range of statistical and domain-specific techniques, and tools like ggplot2 are renowned for the quality of their graphics.
Key characteristics
R is dynamically typed (see static vs dynamic typing), interpreted, and garbage-collected, with a functional and array-oriented bent.2 Its strengths are also its limits: it is purpose-built for statistics, so it is less comfortable as a general-purpose language, and pure-R loops are slow, pushing heavy work into vectorised or native code. For numerical and data work it competes with Python (which has a larger general ecosystem) and the faster Julia; for engineering signal work many reach for MATLAB instead.
Sources
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R (programming language) — Wikipedia, for history, origins, and statistical focus. ↩
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The R Project for Statistical Computing — official site, documentation, and the CRAN ecosystem. ↩ ↩2