R free for PC, Mac

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  • Developer The R Foundation
  • Version 4.3.1
  • License Open Source
  • Language en

R is a versatile and efficient programming language designed for statistical graphics and computing. It can handle a large amount of data for statistical computing, comes with an extensive library of additional packages, and can be run on any platform combined with other languages and technologies.

What is R?

R is a programming language for statistical computing and graphics initially designed by Ross Ihaka and Robert Gentleman and still developed by the R Core Team. R is mainly used among data miners, statisticians, and bioinformaticians for data analysis and statistical software development. As an open-source programming language, it is powered by a vast community and tons of additional packages to help you solve your problems efficiently.

What are the key features of R?

  • Powerful graphical capabilities: Clearly and quickly visualizing data is critical. R can produce static graphics with production-quality results thanks to all the vast graphical libraries like Plotly, ggplot2, and many more.
  • Vast packages library: R has CRAN, which stands for Comprehensive R Archive Network, and agglomerates over 10.000 different packages. They are valuable assets as they can help you solve specific problems in various domains like biology, astronomy, physics, industry, etc.
  • Databases-friendly: R comes with several packages tailored to interact easily with databases like RmySQL, Roracle, Open Database Connectivity Protocol, and more.
  • Data structures: It supports various types of data structures, including Vector (collection of elements of the same type, in one dimension), List (collection of elements of various types, in one dimension), Dataframe (basically a table, two-dimensional structure, each row can be a structure of different type), Matrix (rectangular arrangement of numbers in rows and columns), Array (collection of data of the same types stored in more than two dimensions), and Factors (used to categorize data and store it as levels, the inner value of a number or a string, like "TRUE", "JOHN", etc.).
  • Data arithmetic and calculation: It already features all the arithmetic operations to handle the different data structures and perform simple and complex mathematical or statistical calculations on various data. For example, you can perform linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and more. And, of course, it can handle large data sets effortlessly.
© R
  • No compiler: As an interpreted language, you don't need a compiler and wait for long moments before executing your code, but just to run it in real time.
  • Huge community: Over the years, the number of R users has drastically grown to form a vast and active community. Hence, you will always find the help you need, and they even organize various events.
  • Cross-platform: R can be run on any platform, so you can seamlessly port your code, and it will keep working flawlessly.
  • Cross-language: Even though most of your code can be written in R, you can also incorporate C, C++, FORTRAN, Java, .NET, or Python for handling heavy tasks and manipulating objects directly.
  • Cross-technology: You can pair R with distributed computing technologies like Spark and Hadoop. Hence, you can remotely use a Spark cluster to process large datasets and drastically scale data processing.
  • Generate reports: Thanks to R's markdown package, you can quickly and automatically generate reports as Word documents or PowerPoint presentations, and even web pages.

How to use R?

There are plenty of valuable resources on the official website, including manuals for installation, getting started, and more. You can also consult the dedicated FAQs.

Is R free?

Yes, R is free to use.

Is R safe?

Yes, R is considered safe. Base R packages are well-tested, and so are additional packages in CRAN. Still, ensure the additional packages you download are considered safe.