R (programming language) logo

R (programming language)

Enables statistical analysis and graphical representation of data through a wide variety of techniques.

Made by Ross Ihaka and Robert Gentleman

  • statistical

  • data-analysis

  • Statistical Analyzer

  • data-acquisition

  • Programming Language

  • statistical-graphics

  • Research

  • programming

  • statistics

  • data-automation

What is R (programming language)?

R is a powerful and versatile programming language and software environment designed for statistical computing and data visualization. Developed as a GNU project, R shares similarities with the S language but offers a distinct implementation with numerous enhancements. R provides users with a wide range of statistical techniques, including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, and clustering, among others. This extensive set of tools makes R a preferred choice for advanced data analysis and data mining tasks, catering to the needs of users who seek comprehensive control over their data processing and analytical workflows. R's open-source nature and active community ensure a highly extensible platform, with a vast array of user-contributed packages and libraries available to expand its functionality. Whether you are a seasoned statistician, a data scientist, or a researcher, R empowers you to harness the full potential of your data through its robust statistical computing capabilities and dynamic visualization options

Highlights

  • Wide range of statistical techniques: linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and more
  • Highly extensible platform with a vast ecosystem of user-contributed packages and libraries
  • Suitable for advanced users who seek comprehensive control over data processing and analysis
  • Powerful data visualization capabilities to effectively communicate insights

Platforms

  • Windows
  • BSD
  • Mac
  • Linux

Languages

  • English

Features

    • Communities

    • Quantitative data analysis

    • Customizability

    • Data science

    • Support for scripting

    • Automatic data loading

    • Data Mining