{"id":453,"date":"2018-07-13T12:41:01","date_gmt":"2018-07-13T12:41:01","guid":{"rendered":"http:\/\/itp7.epgpbooks.inflibnet.ac.in\/?post_type=chapter&p=453"},"modified":"2019-05-16T09:33:32","modified_gmt":"2019-05-16T09:33:32","slug":"r-programming-1","status":"publish","type":"chapter","link":"https:\/\/ebooks.inflibnet.ac.in\/itp7\/chapter\/r-programming-1\/","title":{"rendered":"R Programming – 1"},"content":{"raw":"
\"epgp<\/a>\r\n<\/span><\/div>\r\n \r\n\r\nOverview of R<\/strong>\r\n\r\n \r\n

R is an open source program licensed under GNU GPL, it is a Software Environment for Statistical Computing . R supports a variety of statistical functions, programming and graphics related utilities. R is widely used by statisticians, data miners and researchers as a statistical tool. Recently, R has gained wide popularity due to the capabilities of machine learning utilities which can be done very easily by importing libraries. R is available for most of the operating systems. R has a command line interface, there are several GUI front-ends that support R.<\/p>\r\n \r\n

R is an effective programming language. R provides a variety of programming features like variables, conditions, loops, user defined recursive functions, datasets facilities. R also has facilities for data handling, calculations, retrieval and strage facilities. R provides a wide range of operators for calculations on arrays, data structures like lists, vectors and matrices. It provides integrated collection of tools for data analysis. R provides graphical facilities for to create charts, plots in desired formats.<\/p>\r\n \r\n\r\nDownload and Installation<\/strong>\r\n\r\n \r\n

R can be downloaded from its website https:\/\/www.r-project.org, <\/a>R is available for most of the operating systems. It is available for Windows in binary form while it can be installed on Red Hat based distributions using the following command:<\/p>\r\n \r\n\r\n$sudo yum install R -y\r\n\r\n \r\n

Alternatively, R can be downloaded as a source code and can be compiled into a package on Unix like systems<\/p>\r\n \r\n\r\nInterface & Other tools<\/strong>\r\n\r\n \r\n

The interface of R can be either in command prompt or there are GUI tools that are made available by third party for programming in R. The following screen shows a command line interface that is available after downloading R from the above-mentioned website:<\/p>\r\n \r\n

\"\"<\/p>\r\n

Figure 1: Default R Console<\/strong><\/p>\r\n \r\n

The default software uses command line interface. We can run commands using the command line interface or execute R scripts using the same interface. Following are few examples of using the command line interface to execute commands and R scripts.<\/p>\r\n \r\n\r\n\"\"\r\n\r\n \r\n

As shown in above screen, R can be started by using 'R' command on $ prompt. A special '>' prompt is seen for R. We can type commands on this prompt one by one and get commands executed. The output will also be generated on the same prompt. R, also supports execution of scripts. The scripts can be typed in text format in some file, say \"first.R\" and it can be executed by issuing the command Rscript on the command prompt. The execution of R scripts is shown below:<\/p>\r\n \r\n

\"\"<\/p>\r\n \r\n\r\nCommands related to R Environment<\/strong>\r\n\r\n \r\n

R provides functions to interact with the environment of system. R has its own default working directory that can be listed using getwd() function. We can also set the working directory to some other desired directory of secondary storage. Through the R command prompt, list of files is also possible using dir() function. The following table shows few widely used functions of R:<\/p>\r\n

\"\"<\/p>\r\n \r\n\r\nPackages in R<\/strong>\r\n\r\n \r\n

The real power of R is hidden in its wide variety of packages. R packages are a collection of R functions, complied code and sample data, the packages are used for specific functionality. They are stored under a directory called \"library\"<\/strong> in the R environment. R comes by default with a set of packages during installation. Depending on the requirement, more packages can be added later, when they are needed for some specific purpose. When we start the R console, only the default packages are available in standard installation.<\/p>\r\n \r\n\r\n\"\"\r\n\r\n \r\n

R provides a variety of packages for executing specialized tasks. There are packages for numerical computing, machine learning, financial calculations, etc. The above table lists functions that can be used to display\/search packages or install additional packages that are not provide in standard installation of R. Functions like help() or help.start() can be used to browse various topics available in the R manual. The above listed commands\/functions can be typed on the command prompt screen as shown in below figure:<\/p>\r\n \r\n

\"\"<\/p>\r\n

Figure 2: Command prompt to execute various functions of R<\/p>\r\n \r\n\r\n \r\n\r\n \r\n\r\nUsing Command Prompt for R programming<\/strong>\r\n\r\n \r\n

Let us go through some example, how command prompt can be used to execute different commands of R. As seen in the below code, the command prompt '>' is used to execute mathematical calculations. Assignment of value to variables can be done using '->' symbol or also by using the assign() function as shown below:<\/p>\r\n

\"\"<\/p>\r\n \r\n\r\nProgramming Support in R<\/strong>\r\n\r\n \r\n\r\nIn R programming, there is a rich set of data type support as in 'C' language. R supports a wide variety of data types that are listed in following table:\r\n

\"\"<\/p>\r\n

Since R is a scientific tool, it supports complex data types and also supports raw data type where the data \u00edtems can be a mix of text and numeric values.<\/p>\r\n \r\n

The following table lists varios operators that are supported by R. As we have already seen, R supports arithmetic operations through command prompt or through scripts. The following operators can be used over variables\/numbers to perform calculations:<\/p>\r\n

\"\"<\/p>\r\nR also supports a rich set of logical operators to carry out comparison of values. The list of logical operators are shown in following table:\r\n

\"\"<\/p>\r\n

\"\"<\/p>\r\nData Structures in R<\/strong>\r\n\r\n \r\n

Data structures are generally used to store multiple \u00edtems using a common variable name. In R, there are two categories of data structures. Data structures that store homogeneous values and those that store heterogeneous values. Data structures supported by R are:<\/p>\r\n\r\n