## When was R language created?

August 1993

R (programming language)

Designed by | Ross Ihaka and Robert Gentleman |

Developer | R Core Team |

First appeared | August 1993 |

Stable release | 4.1.1 / 10 August 2021 |

Influenced by |
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### Who invented R language?

Ross Ihaka

Robert Gentleman

R/Designed by

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, of which Chambers is a member. R is named partly after the first names of the first two R authors and partly as a play on the name of S.

#### What does R language stand for?

statistical analysis, graphics representation and reporting

R is a programming language and software environment for statistical analysis, graphics representation and reporting. This programming language was named R, based on the first letter of first name of the two R authors (Robert Gentleman and Ross Ihaka), and partly a play on the name of the Bell Labs Language S.

**Why is r such a terrible language?**

R is terrible, and especially so for non-professional programmers, and it is an absolute disaster for the applications where it routinely gets used, namely statistics for scientific applications. The reason is its strong tendency to fail silently (and, with RStudio, to frequently keep going even when it does fail.)

**Who uses R?**

R is one of the latest cutting-edge tools. Today, millions of analysts, researchers, and brands such as Facebook, Google, Bing, Accenture, Wipro are using R to solve complex issues. R applications are not limited to just one sector, we can see R programming in — banking, e-commerce, finance and many more.

## Which is basic package of R?

This package contains the basic functions which let R function as a language: arithmetic, input/output, basic programming support, etc. Its contents are available through inheritance from any environment. For a complete list of functions, use library(help = “base”) .

### Where was R invented?

the University of Auckland

A (Brief) History of R R was first implemented in the early 1990’s by Robert Gentleman and Ross Ihaka, both faculty members at the University of Auckland. Robert and Ross established R as an open source project in 1995. Since 1997, the R project has been managed by the R Core Group.

#### Is R easier than Python?

Learning curve Both Python and R are considered fairly easy languages to learn. Python was originally designed for software development. If you have a background in statistics, on the other hand, R could be a bit easier. Overall, Python’s easy-to-read syntax gives it a smoother learning curve.

**Why is it called R?**

In 1991 Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, began an alternative implementation of the basic S language, completely independent of S-PLUS. R is named partly after the first names of the first two R authors and partly as a play on the name of S.

**Is Python easier than R?**

## Where is R most used?

R is primarily used for descriptive statistics. Descriptive statistics summarize the main features of the data. R is used for a variety of purposes in summary statistics like central tendency, measurement of variability, finding kurtosis and skewness. R is most widely used for exploratory data analysis.

### What is your in computer language?

,

#### Is the your programming language useful?

R is one of the most useful programming languages which is cross-platform that means it can seamlessly run on different operating systems. In R, quality of some packages is not up to the mark R does not have the best memory management. Therefore, it may consume all available memory.

**What is are in software?**

R is an integrated suite of software facilities for data manipulation, calculation and graphical display. a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.

**What is are data software?**

R Software Environment Open Source – Free Software Provides a wide variety of Statistical (linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering) and Graphical Techniques Effective data handling and storage facility Suite of operators for calculations on arrays, in particular matrices