News:

MyKidsDiary.in :: Capture your kids magical moment and create your Online Private Diary for your kids

Main Menu

R programming language Tutorial

Started by NiveRoshni, Aug 08, 2020, 03:22 PM

Previous topic - Next topic

NiveRoshni

R programming language is one of the most commonly used programming languages for Data Analysis and Machine Learning. R provides an excellent framework and built-in libraries to develop powerful Machine Learning algorithms. R is also used for general statistical computing as well as graphics. R has been well adopted by enterprises. Those who wish to join "Analytics" team of a large organization should definitely learn R.

Pros:

Ability to run seamlessly on various operations systems

Active, mushrooming community

Being open-source and free grants the ability to make tweaks as per the requirements

Comprehensive statistical analysis language

Highly extensible

Powerful package ecosystem

Cons:

Lacks security features

No strict programming guidelines

Poor memory management

Quality of some packages is subpar

Why use R for statistical computing and graphics?

R is open-source and free!

R is free to download as it is licensed under the terms of the GNU General Public License. You can look at the source to see what's happening under the hood. There's more, most R packages are available under the same license so you can use them, even in commercial applications without having to call your lawyer.

R is popular – and increasing in popularity

IEEE publishes a list of the most popular programming languages each year. R was ranked 5th in 2016, up from 6th in 2015. It is a big deal for a domain-specific language like R to be more popular than a general-purpose language like C#. This not only shows the increasing interest in R as a programming language, but also of the fields like Data Science and Machine Learning where R is commonly used.

R runs on all platforms

You can find distributions of R for all popular platforms – Windows, Linux and Mac.R code that you write on one platform can easily be ported to another without any issues. Cross-platform interoperability is an important feature to have in today's computing world – even Microsoft is making its coveted .NET platform available on all platforms after realizing the benefits of technology that runs on all systems.

Learning R will increase your chances of getting a job

According to the Data Science Salary Survey conducted by O'Reilly Media in 2014, data scientists are paid a median of $98,000 worldwide. The figure is higher in the US – around $144,000.Of course, knowing how to write R programs won't get you a job straight away, a data scientist has to juggle a lot of tools to do their work. Even if you are applying for a software developer position, R programming experience can make you stand out from the crowd.

R is being used by the biggest tech giants

Adoption by tech giants is always a sign of a programming language's potential. Today's companies don't make their decisions on a whim. Every major decision has to be backed by a concrete analysis of data.

Companies Using R

R is the right mix of simplicity and power, and companies all over the world use it to make calculated decisions. Here are a few ways industry stalwarts are using R and contributing to the R ecosystem.

Run R Programming in Mac

*Go to the official site of R programming

*Click on the CRAN link on the left sidebar

*Select a mirror

*Click "Download R for (Mac) OS X"

*Download the latest pkg binary

*Run the file and follow the steps in the instructions to install R.

Run R Programming in Windows

*xGo to the official site of R programming

*Click on the CRAN link on the left sidebar

*Select a mirror

*Click "Download R for Windows"

*Click on the link that downloads the base distribution

*Run the file and follow the steps in the instructions to install R.

Is R programming an easy language to learn?

This is a difficult question to answer. Many researchers are learning R as their first language to solve their data analysis needs.

That's the power of the R programming, it is simple enough to learn as you go. All you need is data and a clear intent to draw a conclusion based on analysis on that data.

In fact, R is built on top of the language S programming that was originally intended as a programming language that would help the student learn to program while playing around with data.

However, programmers that come from a Python, PHP or Java background might find R quirky and confusing at first. The syntax that R uses is a bit different from other common programming languages.

While R does have all the capabilities of a programming language, you will not find yourself writing a lot of if conditions or loops while writing code in the R language. There are other programming constructs like vectors, lists, frames, data tables, matrices etc. that allow you to perform transformations on data in bulk.