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R Language simplified in 5 minutes

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R Programming Language

R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing.

R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. Polls, surveys of data miners, and studies of scholarly literature databases show that R’s popularity has increased substantially in recent years.

R Programming Language Explained:

R is a programming language and free software environment for statistical computing and graphics. The R language was created in 1993 by statistician Robert Gentleman and software programmer Ross Ihaka. It is supported by the R Foundation for Statistical Computing, a charity whose mission statement includes “to promote the use of, development of, and dissemination of statistical methods based on the current version of the R language.”

1. R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing.

R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing.

  • Run: You can run R from the command line by typing “R”.
  • Quit: You can quit R with q() or ctrl+D.
  • Help: Open help window with ?topic or help(topic). To search for a topic, type ??topic.

2. The R language is widely used among statisticians and data miners for developing statistical software and data analysis.

The R language is widely used among statisticians and data miners for developing statistical software and data analysis. Polls, surveys of data miners, and studies of scholarly literature databases show that R’s popularity has increased substantially in recent years.

R is an implementation of the S programming language combined with lexical scoping semantics inspired by Scheme. S was created by John Chambers in 1976 while at Bell Labs. There are some important differences, but much code written for S runs unaltered under R.

R is named partly after the first names of the first two R authors and partly as a play on the name of S. The project was conceived in 1992, with an initial version released in 1995 and a stable beta version in 2000. It is now developed by the R Development Core Team, of which Chambers is a member.[8]

R is easily extensible through functions and extensions, and the R community is noted for its active contributions in terms of packages.[9] Many of R’s standard functions are written in R itself,[10] which makes it easy for users to follow the algorithmic choices made.[11] For computationally intensive tasks, C, C++, Fortran and Java code can be linked to R,[12] either to manipulate objects without copying them back into R or to create custom distributions such as variations on random number generation.[13][14][15]

3. Polls, surveys of data miners, and studies of scholarly literature databases show that R’s popularity has increased substantially in recent years (1).

Facts about R’s Popularity:

  • R was first released to the public in 1995. Since then, it has become one of the most popular programming languages for data analysis.
  • The TIOBE Index, which ranks programming languages by popularity, shows that R has grown steadily in rank over time and is currently the 5th most popular language in the world (1).
  • An annual survey of more than 2,000 data scientists found that almost 50% of respondents used R as their primary programming language (2).

4. The programming code is available from the project website, but it’s also available from different mirror servers.

The source code of R is available on the project’s website, but it’s also available from several mirror servers. These mirrors are located in different geographic zones to make downloads faster and more reliable. You can find a list of all mirrors on the project website.

For example, suppose you live in Australia and the main server is in Seattle. If there is a mirror server in Sydney, then using that mirror would be much quicker than downloading everything from Seattle.

5. Its syntax is very similar to the S programming language which was developed at Bell Labs (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues.

The following are some other notable programming languages and their similarities to R:

  • C – R shares the C-style syntax for control structures (e.g., if-else, for, while) and function & argument declarations.
  • SR syntax is very similar to the S programming language which was developed at Bell Labs (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues.
  • SAS – R has a vast number of libraries that allow it to be implemented in SQL, Perl, XML, HTML, CSS, and even Markdown.

6. It provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering) and graphical techniques, and is highly extensible (1).

What is R?

R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. Polls, surveys of data miners, and studies of scholarly literature databases show that R’s popularity has increased substantially in recent years.

R is a GNU package. The source code for the R software environment is written primarily in C, Fortran, and R.

R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team.

R programming language can be used to do statistical analysis of data sets

R is an open-source language, meaning that its source code is available to the public. This makes it easy for anyone who wants to use R. As a result, there is a large community of R users and numerous resources available online.

Because of these resources, R is easy to learn, even if you have not previously used any programming languages. The syntax in R is straightforward and similar to other languages like Python or JavaScript. Additionally, R is a high-level language so you do not need to worry about low-level details like memory management or pointers. Finally, R can be used as both an object-oriented language and a functional language which makes it highly flexible for different tasks.

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