R programming language - Introduction

R It's an open source programming language , It is widely used as statistical software and data analysis tools .R Usually with a command line interface .R Can be found in Windows、Linux and macOS And other widely used platforms . Besides ,R Programming languages are the latest cutting-edge tools .

It was developed by the University of Auckland, New Zealand Ross Ihaka and Robert Gentleman Design , At present by R Development Core Team Development .R The programming language is S An implementation of programming language . It also combines Scheme Inspired lexical scope semantics . Besides , The project was conceived in 1992 year ,1995 The initial version was released in ,2000 A stable beta version was released in .

Why choose R programing language ？

• R Programming is used as machine learning 、 The main tools of statistics and data analysis .R You can easily create objects 、 Functions and packages .

• It is a platform independent language . This means that it can be applied to all operating systems .

• It is an open source free language . This means that anyone can install it in any organization , Without having to buy a license .

• R Programming languages are more than just statistical packages , It also allows us to communicate with other languages （C、C++） Integrate . therefore , You can easily interact with many data sources and statistical packages .

• R Programming languages have a large user community , And it's growing every day .

• R At present, it is one of the most popular programming languages in the data science job market , This makes it the hottest trend today .

R Features of programming language

R The statistical characteristics of

Basic statistics ： The most common basic statistical term is mean 、 Mode and median . These are called “ Central trend measures ”. So use R Language we can easily measure concentration trends . Static graphics ： R Rich tools to create and develop interesting static graphics .R Contains functions of many drawing types , Including graphic maps 、 Mosaic drawing 、 Double drawing , And the list continues . A probability distribution ： Probability distribution plays an important role in statistics , By using R, We can easily handle various types of probability distributions , For example, binomial distribution 、 Normal distribution 、 Chi square distribution and so on . Data analysis ： It provides a huge platform for data analysis 、 A coherent and integrated set of tools .

R The programming features of

R package ：R One of the main functions of is that it has a wide range of Libraries .R Yes CRAN（Comprehensive R Archive Network）, It is an inclusion of 10、0000 Repository for multiple packages . Distributed computing ： Distributed computing is a model , The components of the software system are shared among multiple computers to improve efficiency and performance . be used for R Two new packages for distributed programming in ddR and multidplyr On 2015 year 11 Published in .

stay R Chinese programming

because R It is very similar to other widely used languages in grammar , So in R It's easier to code and learn in . The program can be used in any widely used IDE（ Such as R Studio、Rattle、Tinn-R etc. ） of use R To write . The program uses the extension .r Save the file . To run the program , Please use the following command on the command line ：

R file_name.r

Example ：

# R program to print Welcome to haiyong.site! # Below line will print "Welcome to haiyong.site!"cat("Welcome to haiyong.site!")

Output ：

Welcome to haiyong.site!

R The advantages of

• R It is the most comprehensive statistical analysis package . Because new technologies and concepts usually appear first in R in .

• because R The programming language is open source . therefore , You can run... Anytime, anywhere R.

• R The programming language is suitable for GNU/Linux and Windows operating system .

• R Programming is cross platform , Can run on any operating system .

• stay R in , Welcome to provide new bags 、 Bug fixes and code enhancements .

R The shortcomings of

• stay R In programming language , The standards of some packages are not perfect .

• although ,R Commands put little pressure on memory management . therefore R Programming languages may consume all available memory .

• Basically , stay R in , If something doesn't work , No one will complain .

• R Programming language ratio Python and MATLAB Other programming languages are much slower .

R Application

• We will R For Data Science . It provides us with a large number of statistical related libraries . It also provides an environment for statistical calculation and design .

• Many quantitative analysts use R As its programming tool . therefore , It helps with data import and cleanup .

• R It's the most popular language . So many data analysts and research programmers use it . therefore , It is used as the basic tool of Finance .

• Now ,Google、Facebook、bing、Twitter、Accenture、Wipro And other technology giants are using R.

R and Python It plays an important role in Data Science . For any novice , stay R and Python Choosing the better or more appropriate one of the two can become confusing . In the next article, I will introduce ：R vs Python Choose which language is more suitable for Data Science .