R Studio Download in Simple Steps.

Pinnacle of programming languages of it’s kind, R is an extremely used for statistical computing and data analytics. With applications in numerous streams of engineering and finance, this has grown into a huge platform with complex packages and unparalleled utility. We will now see how R Studio can be downloaded on various operating systems and initialising the software to maximize it’s potential.

We need to install R and R studio from different websites, to get started. R is the programming language required for statistical calculations and R studio is an integrated development environment ( IDE ) that helps us develop programs in R.

R can be downloaded from Comprehensive R Archive Network or CRAN. We can reach this website at. CRAN or by simply searching for CRAN on google. The home website has three primary links; Download R Linux, Download R windows, Download R mac, among others, from which we can get the required source file to install R. Alternatively we can select mirrors from the menu and search for our country. In this way, we can find specific versions of the programming language needed. Upon selecting a version of R for a specific platform, we will be redirected to a page which has several subdirectories. We need to select ‘ install R for the first time ‘ and then, ‘ Download R for windows ‘ ( or the required OS ) to the download started.

To download R studio, one must reach R studio site at

R Studio Site. This will directly take us to a page with a couple of versions of R studio. The open source license for R studio desktop is available for free and can be selected from the options in the page. This takes us to a list of options for various platforms. We can select from R studio windows, R studio Ubuntu, R studio mac accordingly, and get our download started.

The next step is to install R from the downloaded file, which is pretty straightforward and self-directory, once we open the downloaded file. This goes the same to install R on windows, install R on mac or to install R on Linux.

R is only as good as the packages it has. Packages are collections of functions, data and compiled-code in a well-defined format. These make R extremely functional and very easy to use. R usually comes with a standard set of packages, but there are over 10,000 packages available to download. We will get into installing some of the very useful and necessary packages in Business Analytics and data science.

Ways to Install & Attach Packages.

There are broadly two ways to install and attach the packages, once we start R studio. One of them is by using the code, which can be seen on the left side of the screen. Another way is to make use of the graphical console on the right side of the screen.

To install packages in R using a code, we need to simply write the code required to install and then further to attach the specific package we would like. The code to install a package is as follows

install.packages(“package name”)

and then we press enter to execute the line of code. The package name is the required package we wish to install. For example, to install a package named ‘refine’, the code will be as follows;

install.package(“refine”)

Upon pressing enter, we get prompts on the screen that the command is running, and finally, a prompt that states the required package is installed.

Now that we have installed our required packages, we need to attach the package to the library. Attaching the package to the library enables the respective commands functional. To attach a package through the command line, we need to use the following code

library(“package name”)

For example, to attach the previously installed ‘refine’ package, the command would be

library(“refine”)

R studio also has a graphical interface that can help us install R packages and attach R packages to our library. The right section of our screen has a tab named packages, selecting which, gives us a list of packages already installed. We can also make use of the search bar to search for the installed packages.

To install any new package, we need to select the install button. This opens up a dialogue box, with an empty field headed ‘Packages’. We need to enter our package name in the field and click install to install our required package. Example, if we need to install the package ‘lmtest’ then we write lmtest in the field and click install. The prompt in command lines will show us that the package is installed.

And now to attach the required package to our library, we need to simply select the box next to

package name in the list. This will automatically attach the package and get it started.

Now that we know how to install r packages and attach them to our library, we will now take a look into the required packages that are fundamentally used:

reshape, car, sandwich, lmtest, party, rpart, amap, arules, arulesSequences, basket_rules, tseries, forecast, glmgraph, ineq.

The process of installing and attaching these packages are same as described, and with these, you will be exhaustively equipped with the maximum functionality of R.