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Interesting Facts about R Programming Language

Last Updated : 09 Feb, 2023
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R is an open-source programming language that is widely used as a statistical software and data analysis tool. R generally comes with the Command-line interface. R is available across widely used platforms like Windows, Linux, and macOS. Also, the R programming language is the latest cutting-edge tool. It was designed by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team. Interesting-Facts-about-R-Programming-Language Here are some interesting facts about the R programming language:

  • R programming language is an implementation of the S programming language. It also combines with lexical scoping semantics inspired by Scheme. It is named partly after the first names of the first two R authors and partly as a play on the name of S.
  • R supports both procedural programming and object-oriented programming. Procedural programming includes the procedure, records, modules, and procedure calls. While object-oriented programming language includes class, objects, and generic functions.
  • R language is an interpreted language instead of a compiled language. Therefore, it doesn’t need a compiler to compile code into an executable program. This makes running an R script much less time-consuming.
  • The number of R packages available either through CRAN or GitHub is 1, 00, 000 and they do epic stuff with just one line of code. It could range from Regression to Bayesian analysis.
  • R is growing faster than any other data science language. It’s the most-used data science language after SQL. It is used by 70% of data miners.
  • One of the packages in R namely rmarkdown package helps you create reproducible Word documents and reproducible Powerpoint Presentations from your R markdown code just by changing one line in the YAML! (“YAML Ain’t Markup Language!”)
  • It is really very easy in R to connect to almost any database using the dbplyr package. This makes possible for an R user to work independently and pulling data from almost all common database types. You can also use packages like bigquery to work directly with BigQuery and other high-performance data stores.
  • You can build and host interactive web apps in just a few lines of code in R. Using the flexdashboard package in R you can create interactive web apps with a few lines of code. And using the rsconnect package you can also host your web apps on your own server or, even easier, host them on a cloud server.
  • You can not only deploy web apps but also can make them into awesome video games in R. The nessy package helps you create NES(The Nintendo Entertainment System) looking Shiny apps and deploy them just like you would any other Shiny app.
  • You can build APIs and serve them from R. The plumber package in R helps you convert R functions to web APIs that can be integrated into downstream applications.
  • According to PYPL PopularitY of Programming Language R is #7 of all programming languages. R is the #1 Google Search for Advanced Analytics software. It has more than 3 million users worldwide make a huge community for R programming language.
  • The origin of R programming language can be traced back to 1993 when Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand introduced it.
  • R is an open-source language and it is available for free for everyone to use for statistical and graphical purposes.
  • The R programming language has a supportive and enthusiastic user community, providing ample resources and assistance to users.
  • The widespread usage of R in fields such as data science, machine learning, and statistical modeling has made it one of the most sought-after programming languages.
  • R has a wealth of packages and libraries, allowing users to perform complex tasks easily and extend its functionality.
  • Industries such as finance, healthcare, pharmaceuticals, and marketing make use of R for data analysis and modeling.
  • In academic research, R has become a crucial tool across various disciplines such as biology, psychology, and economics.
  • R operates seamlessly on different platforms like Windows, macOS, and Linux, making it easily accessible to users regardless of the operating system they use.

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