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.
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
rmarkdownpackage 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
dbplyrpackage. 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
bigrqueryto 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
flexdashboardpackage in R you can create interactive web apps with a few lines of code. And using the
rsconnectpackage 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
nessypackage 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
plumbrpackage 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.
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