Deep Diving into R

     R Installation

The latest version of R can be downloaded from http://cran.r-project.org/bin/windows/base/

You will be asked whether you want to save or run a file “R-3.2.0-win.exe”. Choose “Save” and save the file on the Desktop. Then double-click on the icon for the file to run it and install R.

RStudio

RStudio is the Integrated Development Environment for R. It comes in two varieties namely:

a) RStudio Desktop: RStudio Desktop is a standalone desktop application. It can be downloaded from the following link: http://www.rstudio.com/products/rstudio/download/.

b) RStudio Server: It is a Linux server application that provides a web browser based interface to the version of R running on the server. It is necessary for:

• Computations that require larger CPU utilization
• Efficient utilization of resources
• Usage of standardized R package versions

Installing R packages

Choose Install Packages from the Packages menu in Rstudio.

Select a CRAN mirror.

Choose the package.

Use library (package) function to load it for use. 

Getting Help

R has built in help system. The following commands can be used to access it:

help.start()                          # for general help

help(mean)                         # help about the function mean

?mean

apropos("str")                     # lists all functions containing the string “str”

example(mean)                   # shows an example of mean ()

vignette(“mean”)                  #Show vignette for mean

Key Objects

R mainly supports two types of objects:

Basic Objects

Important basic objects are:

• Atomic Vector: All the elements of an atomic vector should be of the same type. Based on the type of values it contains atomic vector can be differentiated into three types namely numeric vector, logical vector and character vector.
• List: Lists can have atomic vectors or other lists as components.

Derived Objects

Following are the derived objects in R:

• Matrix: All elements of the matrix should be of the same type.
• Data frame: It can have different data types in different columns.
• Factors: Factors contain categorical data. 

Data Import and Export

R can read different types of files e.g. plain text files, databases, Excel files, XML, HTML files, SPSS, SAS and Stata formatted data. The data in R can be exported in all these formats.

Developing Web applications in R

Shiny is a powerful framework used for building interactive web applications using R. A Shiny application is defined by two files namely ui.R and server.R. The file ui.R contains the definition of the application interface and server.R contains the code for the computation.