r语言是高级编程语言_什么是R编程？

r语言是高级编程语言

什么是R编程？ (What is R Programming?)

R is one of the most popular scripting languages for statistical programming today. The demand of R programmers has been constantly on the rise since the early 2010s and R still enjoys the status as a go-to programming language among data scientists.

R是当今统计编程中最受欢迎的脚本语言之一。自2010年代初以来，R程序员的需求一直在不断增长，并且R仍然在数据科学家中享有作为编程语言的地位。

R has also been adapted to deep learning these days and this helped several statisticians take on to deep learning in their respective fields easily, making R an indispensable part of the current burgeoning AI scenario.

如今，R也已经适应深度学习，这帮助了一些统计学家轻松地在各自领域进行深度学习，这使得R成为当前蓬勃发展的AI场景中不可或缺的一部分。

Recommended Read: Python Data Science Libraries

推荐阅读 ： Python数据科学库

R编程语言的历史 (History of R Programming Language)

R has a precursor named S (S stands for statistics) language, developed by AT&T for statistical computation. AT&T began its work on S in 1976, as a part of its internal statistical analysis environment, which was earlier implemented as FORTRAN libraries.

R具有由AT＆T开发的用于统计计算的名为S （S表示统计）语言的前体。作为其内部统计分析环境的一部分，AT＆T于1976年开始从事S方面的工作，该环境之前已作为FORTRAN库实施。

The man behind S was John Chambers. The single-letter name S was inspired by the ubiquitous C language for programming at the time.

S背后的那个人是约翰·钱伯斯。单字母名称S受到当时普遍使用的C语言编程的启发。

R was developed by Ross Ihaka and Ross Gentleman in a project that was conceived in 1992 at the University of Auckland, New Zealand. The first version was released in 1995 and the first stable beta version came up in the year 2000.

R由Ross Ihaka和Ross Gentleman在1992年由新西兰奥克兰大学构思的项目中开发。 1995年发布了第一个版本，2000年发布了第一个稳定的beta版本。

R initially differed from S as it added lexical scoping semantics on top of the existing S functionalities. The mono-letter name R was inspired by S again, taking the first letter of both the authors’ first names.

R最初与S不同，因为R在现有S功能的基础上增加了词法作用域语义。单字母名称R再次受到S的启发，取了两位作者名字的首字母。

R was developed under GNU public license and openly distributable.

R是在GNU公共许可证下开发的，可以公开分发。

S programming language was later developed into S-plus by TIBCO corporation that bought it from AT&T, by adding some advanced analytical abilities and OOP capabilities.

S编程语言后来由TIBCO公司开发成S-plus，该公司通过添加一些高级分析功能和OOP功能从AT＆T购买了它。

R编程的特点 (Features of R Programming)

Platform independent – Runs on several computing platforms such as Windows, Linux, and Mac OS.
独立于平台 –在Windows，Linux和Mac OS等多种计算平台上运行。
Portable – Easy to run on mobiles, tablets and gaming consoles.
便携式–易于在手机，平板电脑和游戏机上运行。
Frequent releases – Resulting in timely bug fixes and less frustration.
频繁发布–及时修复错误并减少挫败感。
Superior Graphics – Compatibility with aesthetic graphical libraries like ggplot2 and plotly ensures publication-quality graphics visualizations.
卓越的图形–与美观的图形库（如ggplot2）兼容，并以绘图方式确保出版物质量的图形可视化。
Versatility – Hundreds of packages for specific purposes being developed and improved on a daily basis by the developer community.
多功能性 –开发人员社区每天都会开发和改进数百个用于特定目的的软件包。

R Programming Features

R编程功能

R编程的优点 (Advantages of R Programming)

R still remains more dominantly used statistical programming language compared to S and S-plus, and rightly so, owing to many of its virtues.

与S和S-plus相比，R仍然是统计编程语言中使用最广泛的语言，这是正确的，因为它具有许多优点。

R was developed with the intention of building an open-source implementation of S, therefore R is and will always remain an open-source software.
R的开发旨在构建S的开源实现，因此R并将永远是一个开源软件。
R has thousands of professional scientists and statisticians constantly using and improving it.
R有成千上万的专业科学家和统计人员不断地使用和改进它。
R is compatible with Windows, Mac, and Linux. It runs almost anywhere and doesn’t consume much space.
R与Windows，Mac和Linux兼容。它几乎可以在任何地方运行，并且不会占用太多空间。
In addition to the statistical processing features, R can also be used as a general programming language with functional programming and object-oriented programming capabilities.
除了统计处理功能外，R还可以用作具有功能编程和面向对象编程功能的通用编程语言。
R has far more superior visualization features compared to several commercial products, due to the involvement of ggplot2 and plotly.
由于ggplot2和plotly的参与，与几种商业产品相比，R具有更好的可视化功能。
The graphics provided by R are more beautiful and preferred by experts all over the world.
R提供的图形更加美观，并且受到全世界专家的青睐。
R isn’t an innately graphical user interface based environment. It only takes commands as inputs, making it easy to save commands as scripts and port across domains.
R不是与生俱来的基于图形用户界面的环境。它仅将命令作为输入，因此可以轻松地将命令另存为脚本和跨域的端口。
R sessions are efficiently managed. Your command history and data are saved between sessions, therefore you can pick up where you left with little hassle.
R会话得到有效管理。您的命令历史记录和数据将在会话之间保存，因此您可以轻松地从离开的地方接起。
R has a rich and responsive online developer community.
R具有丰富且响应Swift的在线开发人员社区。

R的局限性 (Limitations of R)

R is thought to be the least disliked programming language. Despite all its advantages, R is far from perfect, like any other language. Before plunging into learning R, it will be useful to keep the shortcomings in mind.

R被认为是最不喜欢的编程语言。尽管具有所有优点，但R与其他语言一样远非完美。在投入学习R之前，记住这些缺点将很有用。

Steep Learning Curve: R is not an easy language to get started with. Beginners find it hard to get their feet wet due to the command-line interface. IDEs like RStudio will help overcome this limitation to some extent. Additionally, the wide array of packages can be confusing to beginners.
陡峭的学习曲线 ：R不是一门容易上手的语言。初学者发现由于命令行界面的原因，很难弄湿自己的脚。像RStudio这样的IDE将在某种程度上帮助克服这一限制。此外，各种各样的软件包可能会使初学者感到困惑。
Hungry for Physical Memory: Unlike its strong contender Python, R stores all its data in the physical memory. This makes it hard to handle huge datasets. But fortunately, Hadoop integration for R has improved a lot these days, alleviating the issue to a large extent.
渴望物理内存 ：与强大的竞争者Python不同，R将所有数据存储在物理内存中。这使得难以处理庞大的数据集。但是幸运的是，最近针对R的Hadoop集成已经有了很大的改善，在很大程度上减轻了该问题。
Slower execution: R would need a lot of optimization before your code can run as fast as it does on MATLAB or Python. A strong understanding of the internal working of objects is needed when designing a program to avoid slow execution.
执行速度较慢 ：R需要大量优化，才能使代码像在MATLAB或Python上一样快地运行。在设计程序时，需要对对象的内部工作有深入的了解，以免执行缓慢。

R的可用性 (Availability of R)

R is available as a command-line interface environment at CRAN project (standing for Comprehensive R Archive Network). However, as a beginner you will learn faster with the help of an IDE, of which there are quite a few for R.

在CRAN项目中，R作为命令行界面环境可用（代表“全面的R存档网络”）。但是，作为初学者，您将在IDE的帮助下更快地学习，其中有很多R语言。

RStudio : The most popular IDE for getting started with R. There are both desktop and enterprise versions available.
RStudio ：R入门最流行的IDE。提供桌面版本和企业版本。
StatET : An Eclipse-based IDE for R programming and package building.
StatET ：用于R编程和程序包构建的基于Eclipse的IDE。
ESS-R project: Supports several statistical packages in addition to R, such as S-Plus, SAS, Stata and OpenBUGS/JAGS.
ESS-R项目：除R外，还支持其他统计软件包，例如S-Plus，SAS，Stata和OpenBUGS / JAGS。