Introduction to R
R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S.
The R environment
R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes
What is R in computer?
R is an interpreted language; users typically access it through a command-line interpreter. If a user types 2+2 at the R command prompt and presses enter, the computer replies with 4, as shown below:
What is R in computer science?
R is a programming language and free software environment for statistical computing and graphics supported by the R Core Team and the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis.
What is R journal?
The R Journal is the open access, refereed journal of the R project for statistical computing. It features short to medium length articles on the use and development of R, including packages, programming tips, CRAN news, and foundation news.
What is the main implementation of R?
The main R implementation is written in R, C, and Fortran, and there are several other implementations aimed at improving speed or increasing extensibility. A closely related implementation is pqR (pretty quick R) by Radford M. Neal with improved memory management and support for automatic multithreading. Renjin and FastR are Java implementations of R for use in a Java Virtual Machine. CXXR, rho, and Riposte are implementations of R in C++. Renjin, Riposte, and pqR attempt to improve performance by using multiple processor cores and some form of deferred evaluation. Most of these alternative implementations are experimental and incomplete, with relatively few users, compared to the main implementation maintained by the R Development Core Team.
What are the capabilities of R?
The capabilities of R are extended through user-created packages, which allow specialised statistical techniques, graphical devices, import/export capabilities, reporting tools ( RMarkdown, knitr, Sweave ), etc. The large number of packages available for R, and the ease of installing and using them, has been cited as a major factor in driving the widespread adoption of the language in data science. The R packaging system is also used by researchers to create compendia to organise research data, code and report files in a systematic way for sharing and public archiving.
What is a scalar in R?
Instead, a scalar is represented as a vector with length one. Many features of R derive from Scheme. R uses S-expressions to represent both data and code. Functions are first-class and can be manipulated in the same way as data objects, facilitating meta-programming, and allow multiple dispatch.
What is R used for?
R is a programming language and free software environment for statistical computing and graphics supported by the R Core Team and the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis.
What is R used for?
In retail and e-commerce, R is used for risk assessment and to create marketing strategies. For example, R's machine learning capabilities are used to improve cross-selling and suggest better-related products at checkout to increase profits and sales. R is also used for sales modeling and targeted advertising in retail.
What is R programming?
R is a programming language created by statisticians for statistics, specifically for working with data. It is a language for statistical computing and data visualizations used widely by business analysts, data analysts, data scientists, and scientists. Let's look at more details of the R language to see what makes it different.
What is the purpose of R in the FDA?
In addition, the FDA uses R to evaluate drugs, perform pre-clinical trials, and predict possible reactions caused by the food products they review.
What is R unique?
R is unique in that it is not general-purpose. It does not compromise by trying to do a lot of things. It does a few things very well, mainly statistical analysis and data visualization. While you can find data analysis and machine learning libraries for languages like Python, R has many statistical functionalities built into its core.
Why is R used in banking?
R is used at many of these types of companies because money and statistics go hand-in-hand. Banks use the R language to create credit risk models and conduct other types of risk analysis. It is also used for fraud detection, mortgage modeling, volatility modeling, client assessment, and loan stress test simulations.
What is R programming?
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 ...
What is the major feature of R?
R Packages: One of the major features of R is it has a wide availability of libraries. R has CRAN (Comprehensive R Archive Network), which is a repository holding more than 10, 0000 packages.
Why is R used in statistics?
It gives us a broad variety of libraries related to statistics. It also provides the environment for statistical computing and design. R is used by many quantitative analysts as its programming tool. Thus, it helps in data importing and cleaning. R is the most prevalent language.
What are the features of R?
Statistical Features of R: Basic Statistics: The most common basic statistics terms are the mean, mode, and median. These are all known as “Measures of Central Tendency.”. So using the R language we can measure central tendency very easily.
Is R programming open source?
As new technology and concepts often appear first in R. As R programming language is an open source. Thus, you can run R anywhere and at any time. R programming language is suitable for GNU/Linux and Windows operating system. R programming is cross-platform which runs on any operating system.
Is R a platform independent language?
Objects, functions, and packages can easily be created by R. It’s a platform-independent language. This means it can be applied to all operating system. It’s an open-source free language. That means anyone can install it in any organization without purchasing a license.
Does R use memory?
Although, R commands give little pressure to memory management. So R programming language may consume all available memory. In R basically, nobody to complain if something doesn’t work.
What is the R number?
The R number is a key factor in gauging the coronavirus pandemic. It refers to the 'effective reproduction number' of COVID-19. An R value of 1 is a crucial threshold.
What does R mean in a virus?
R refers to the “effective reproduction number” and, basically put, it’s a way of measuring an infectious disease’s capacity to spread. The R number signifies the average number of people that one infected person will pass the virus to. The R number isn’t fixed, but can be affected by a range of factors, including not just how infectious ...
What does a 0.5 R mean?
An R of 0.5 means that 100 people would infect only 50, who would infect 25, who would infect 13. As the number of cases drops and ill people either die or recover, the virus will be brought under control – as long as the R can be kept low.
How much did R drop in Germany during lockdown?
Lockdown helped drop Germany’s R down to about 0.7 in early April, but researchers at the Robert Koch Institute in Berlin said it had recently increased back to 0.9, before sinking again to 0.75. Even within lockdown, if people start losing patience with restrictions or need to go out to work, R could quickly rise again.
Overview
R is a programming language for statistical computing and graphics supported by the R Core Team and the R Foundation for Statistical Computing. Created by statisticians Ross Ihaka and Robert Gentleman, R is used among data miners, bioinformaticians and statisticians for data analysis and developing statistical software. Users have created packages to augment the functions of the R lang…
History
R is an open-source implementation of the S programming language combined with lexical scoping semantics from Scheme, which allow objects to be defined in predetermined blocks rather than the entirety of the code. S was created by Rick Becker, John Chambers, Doug Dunn, Jean McRae, and Judy Schilling at Bell Labs around 1976. Designed for statistical analysis, the language is an interpreted language whose code could be directly run without a compiler. Many programs writte…
Features
R's data structures include vectors, arrays, lists, and data frames. Vectors are ordered collections of values and can be mapped to arrays of one or more dimensions in a column major order. That is, given an ordered collection of dimensions, one fills in values along the first dimension first, then fill in one-dimensional arrays across the second dimension, and so on. R supports array arithmetics and in this regard is like languages such as APL and MATLAB. The special case of a…
Packages
R's capabilities are extended through user-created packages, which offer statistical techniques, graphical devices, import/export, reporting (RMarkdown, knitr, Sweave), etc. These packages and their easy installation and use has been cited as driving the language's widespread adoption in data science. The packaging system is also used by researchers to organize research data, code and report files in a systematic way for sharing and archiving.
Interfaces
Various applications can be used to edit or run R code.
Early developers preferred to run R via the command line console, succeeded by those who prefer an IDE. IDEs for R include (in alphabetical order) Rattle GUI, R Commander, RKWard, RStudio, and Tinn-R. R is also supported in multi-purpose IDEs such as Eclipse via the StatET plugin, and Visual Studio via the R Tools for Visual Studio. Of these, RStudio is the most commonly used.
Implementations
The main R implementation is written in R, C, and Fortran. Several other implementations aimed at improving speed or increasing extensibility. A closely related implementation is pqR (pretty quick R) by Radford M. Neal with improved memory management and support for automatic multithreading. Renjin and FastR are Java implementations of R for use in a Java Virtual Machine. CXXR, rho, and Riposte are implementations of R in C++. Renjin, Riposte, and pqR attempt to impr…
Communities
R has local communities worldwide for users to network, share ideas, and learn.
A growing number of R events bring users together, such as conferences (e.g. useR!, WhyR?, conectaR, SatRdays), meetups, as well as R-Ladies groups that promote gender diversity. The R Foundation taskforce focuses on women and other under-represented groups.
useR! conferences
The official annual gathering of R users is called "useR!". The first such event was useR! 2004 in May 2004, Vienna, Austria. After skipping 2005, the useR! conference has been held annually, usually alternating between locations in Europe and North America. History:
• useR! 2006, Vienna, Austria
• useR! 2007, Ames, Iowa, US