R (programming language)

R is a programming language and software environment for statistical computing and graphics. Its open-source implementation combines interactive data analysis with a large ecosystem of contributed packages.

R data frames: A two-dimensional R data structure whose columns can hold different types of data and whose rows represent observations. They are R’s standard structure for rectangular datasets used in analysis.
ggplot2: An R package for building layered statistical graphics using a grammar of graphics. It is a widely used system for exploratory and publication-quality plots.
S programming language: A programming language for statistical computing developed at Bell Laboratories in the 1970s. R adapts many ideas and conventions from this influential predecessor.
Python (programming language): A general-purpose programming language widely used in software development, data analysis, and machine learning. Python overlaps with R in data science but serves a broader range of software tasks.
Statistical computing: The use of computational methods and software to analyze data and perform statistical inference. R is a general-purpose environment built specifically around this activity.
R vector: An ordered collection of elements of one basic type, such as numeric, logical, or character values, in R. Vectorized operations let R apply many computations without explicit loops.
Shiny: An R package for creating interactive web applications directly from R. It turns analyses into interactive tools without requiring a separate web framework.
Ross Ihaka: A New Zealand statistician and computer scientist who co-created R with Robert Gentleman. His work at the University of Auckland began the R project.
Julia (programming language): A high-level programming language designed for numerical and scientific computing with performance-oriented compilation. Julia targets scientific computing while seeking more speed than typical interpreted workflows.
Data science: An interdisciplinary practice that uses computing, statistics, and domain knowledge to extract insight from data. R is one of the major languages used across data science workflows.

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Open Database ConnectivityRelated: R packages can use ODBC to query databases from analysis workflows.