Rachel Cole

Rachel Cole


A Complete Guide to Learn R

R Programming Technology is an open source programming language. Also, the R programming language is the latest cutting-edge tool. R Basics is the hottest trend. Moreover, the R command line interface (C.L.I) consists of a prompt, usually the > character.

History of R

John Chambers and colleagues developed R at Bell Laboratories. Basically, R programing language is an implementation of the S programming Language. Also combines with lexical scoping semantics inspired by Scheme. Although, R was named partly after the first names of two R programming language authors. Moreover, the project conceives in 1992, with an initial version released in 1995 and a stable beta version in 2000.

Install R Programming Language & R Studio

In this R tutorial, we are moving towards installations of R Programming and R Studio:

We have to follow three basic steps in the same order to run R programming language and R Studio on your system.

  • R Installation
  • Installation of R Studio
  • Install R Packages.

a. How to Install the R Programming Language?

In respect to the operating system we are using we have to follow the below-mentioned steps:

  • For Mac

First, we have to download the appropriate version of the .pkg file form the following link.

Further, open the downloaded .pkg file and Install R.

  • For Linux

For Ubuntu with Apt-get installed, execute sudo apt-get install r-base in terminal.

  • For Windows

Download the binary setup file for R from the following link.

Open the downloaded .exe file and Install R.

b. How to Install R Studio?

Choose the appropriate installer file for your operating system. Afterward, download it and then run it to install R-studio.

c. How to Install R Packages?

We require a particular package to be installed if we need to use R studio. Further, follow the instructions below:

Run R studio

Afterward, we need to click on the packages tab in the bottom-right section. Once, you complete this then click install. Thus, the dialog box will appear.

In the install packages dialog, write the package name you want to install the Packages field. And then click install. This will install the package you searched for. Either give you a list of matching package based on your package text.

Thus, the installation procedure for R Studio.

Why R Programming Language?

In this R Tutorial, following points describe reasons to learn R Programming.

  • We use R programming as a leading tool for machine learning, statistics, and data analysis. Objects, functions, and packages are easily created by R. As it is used anywhere. Also, it’s platform- independent and free. Thus, anyone can install it in any organization without purchasing a license. Moreover, it can be applied to all operating system.

  • R programming language is not only a statistic package. Also, R allows us to integrate with other languages (C, C++). Thus, you can easily interact with many data sources and statistical packages. As a result, the R programming language has a large growing community of users.

R For Business

R is best for business because it’s an open source. Also, it’s great for visualization. Moreover, the R programming language has far more capabilities as compared to earlier tools. Also, companies are using R programming as their platform and recruit trained users of R.

Features of R Programming Language

These are some R features:

a. Statistics Features of R Programming Language

  • Basic Statistics: Mean, variance, median.
  • Static graphics: Basic plots, graphic maps.
  • Probability distributions: Beta, Binomial.

b. Programming Features of R

  • Distributed Programming
  • R Packages

Why is R Popular?

  • Nowadays, the R programming language is considered as a popular analytic tool in the world. Also, estimates of some users range from 250000 to over 2 million.
  • Basically, R programming language was again the top choice in most of the surveys. As R has more blogs, discussion groups, and email lists than any other tool including SAS Programming.

Job Roles in R Programming Language

Basically, R jobs are not only being offered by IT companies. Although, all types of companies are hiring high paid R candidates including-

  • Financial firms
  • Retail organizations
  • Banks
  • Healthcare organizations etc.

Basically, as we know that there is a huge demand for R jobs among start-ups. Also, companies have several R job openings with various positions like:

  • R data scientist
  • Data scientist(IT)
  • Analyst manager
  • Senior data analyst
  • Business analyst
  • Analyst consultant

Companies Using the R Programming language

R has become the tool of choice for data scientists and statisticians across the world. Also, to predict things like the pricing of their products, etc, companies are using analytics. Below is a list of few companies using R:

  1. TechCrunch
  2. Google
  3. Facebook
  4. Genpact
  5. Bing
  6. Orbitz
  7. ANZ
  8. The New York Times
  9. Thomas Cook
  10. Accenture
  11. Wipro
  12. Mozilla
  13. Novartis
  14. Merck

***“R has slowly won over the hearts of many large corporates”. ***Why Top Companies using R

Job Opportunities for R Statistics Language

Basically, skills that are being valued by the industry shows a lack of understanding. R programming language is a tool, and people can be trained in tools. It is, yet, difficult to train people in Statistics, Data Mining, and Data Analytics, and so on. So there are very good job opportunities for R experts in India.

R Careers

Obviously! R is the best option as it’s trending so much. Also, the R programming language is being used in Big M.N.C’s to Small-scale companies everywhere. It is also used in NON-IT fields, Government, and Non-government companies.

Future Scope of R Programming

The future scope is very bright. As R programming Language is trending these days. Also, it’s simple to learn for those who are new to the R programming language.

Moreover, the recent average salary of R programming is best so you can think how high it will reach in the future.

Sources of R Jobs

You can check various jobs for R technology at below job portals:

  1. naukri.com
  2. indeed.com
  3. LinkedIn

R Applications

  • Basically, R is the most prevalent language. Thus, many data analysts and research programmers use it. Hence, R is used as a fundamental tool for finance.
  • Basically, R is used by many quantitative analysts as its programming tool. Hence, R helps in data importing and cleaning.
  • We use R for Data Science. it gives us a broad variety of statistics. In addition, R provides the environment for statistical computing and design. Rather R considers as an alternate execution of S.

Advantages and Disadvantages of R

a. Advantages of R Programming language

  • Basically, R is the most comprehensive statistical analysis package. As new technology and ideas often appear first in R.
  • Basically, the R programming language is open-source software. Hence anyone can use and change it.
  • As R programming language is an open source. Thus, we can run R anywhere and at any time, and even sell it under conditions of the license.
  • Basically, the R programming language is good for GNU/Linux and Microsoft Windows. Also, R programming is cross-platform which runs on many operating systems.
  • In R, anyone is welcome to provide bug fixes, code enhancements, and new packages.

b. Disadvantages of R programming language

  • In the R programming language, the quality of some packages is less than perfect.
  • In R basically, no one to complain if something doesn’t work.
  • Basically, R is a software application that many people devote their own time to developing.
  • Although, R commands give little thought to memory management. So R programming language can consume all available memory.

Best R Books

Following are the best Books to learn R Programming Language.

a. A Handbook of programming with R by Garrett Grolemund

Generally, if you are new to R then this is the best book for you. As the language of the book is quite simple to understand and examples can be reproduced easily.

b. The Art of R Programming by Norman Matloff

Basically, this book tells how to do software development. As from basic types and data structures to advanced topics. Also, no statistical knowledge is required. Moreover, your programming skills can range from hobbyist to pro.

c. An Introduction To Statistical Learning With Applications in R by Trevor Hastie and Rob Tibshirani

Even if you don’t have knowledge of R then this book is best. As its good for the theoretical and practical understanding of many important topics.

For Example- machine learning and statistical techniques.

d. Learning RStudio For R Statistical Computing by Mark P.J.van der Loo

Basically, this book was designed for R developers and analysts. Also, only for those people who want to do R statistical development using RStudio functionality. Thus, one can create and manage statistical analysis projects, generate reports and graphics.

e. Practical Data Science with R by Nina Zumel & John Mount

Basically, in this book, an author has focused only on data science methods and their applications in the real world.

f. Advanced R by Hadley Wickham

Basically, this book is about how R language works that creates a difference between the top 3 analytical tool — R vs SAS vs SPSS.

g. R Packages by Hadley Wickham

Basically, this book is made for advanced R programmers who are looking to write their own R Packages. As the author has written documentation on R packages. Also, explains the components of the R package, including unit tests and vignettes.

Hope you like our explanation.


I hope this blog will help you to learn in a very advanced manner. Furthermore, if you have any query in this R Tutorial, feel free to ask in the comment section.

#r #python #data-science #data-analysis

What is GEEK

Buddha Community

A Complete Guide to Learn R

Machine learning with R Online Coaching in Chennai

Machine learning with R Training in Chennai is provided by the No.1 Machine learning with R Training in Chennai with experienced trainers.

#machine learning with r training #machine learning with r courses #machine learning certification training #machine learning with r onlineclass

August  Larson

August Larson


R vs Python: What Should Beginners Learn?

Let go of any doubts or confusion, make the right choice and then focus and thrive as a data scientist.

I currently lead a research group with data scientists who use both R and Python. I have been in this field for over 14 years. I have witnessed the growth of both languages over the years and there is now a thriving community behind both.

I did not have a straightforward journey and learned many things the hard way. However, you can avoid making the mistakes I made and lead a more focussed, more rewarding journey and reach your goals quicker than others.

Before I dive in, let’s get something out of the way. R and Python are just tools to do the same thing. Data Science. Neither of the tools is inherently better than the other. Both the tools have been evolving over years (and will likely continue to do so).

Therefore, the short answer on whether you should learn Python or R is: it depends.

The longer answer, if you can spare a few minutes, will help you focus on what really matters and avoid the most common mistakes most enthusiastic beginners aspiring to become expert data scientists make.

#r-programming #python #perspective #r vs python: what should beginners learn? #r vs python #r

Noemi  Sanford

Noemi Sanford


Complete Linear Regression in R | Machine Learning in R | R for Beginners

We are going to learn the introduction of machine learning and linear regression in R 4.0 programming. We will start with the introduction of machine learning then we will discuss the introduction of linear regression. I will also discuss types of linear regression and use cases of linear regression. there are two types of linear regression; simple linear regression and multiple linear regression. Use cases of linear regression are in house price prediction, stock price prediction, Twitter popularity prediction. I will thereafter show you how to analyze the Boston housing dataset. We will analyze dataset variables to understand the variable dependency for the linear regression model. I will show you the linear and non-linear regression models. Thereafter, I will show how you can improve the accuracy of a linear regression model.

#machine-learning #r #r-programming #developer

Annalise  Hyatt

Annalise Hyatt


Learn R the Right Way in 5 Steps — Learn Data Science at Dataquest

R is an increasingly popular programming language, particularly in the world of data analysis and data science. But learning R can be a frustrating challenge if you’re not sure how to approach it.

If you’ve struggled to learn R or another programming language in the past, you’re definitely not alone. And it’s not a failure on your part, or some inherent problem with the language. Usually, it’s the result of a mismatch between what’s motivating you to learn and how you’re actually learning.

This mismatch causes big problems when you’re learning any programming language, because it takes you straight to a place we like to call the cliff of boring.

learn r for data science - the cliff of boring

What is the cliff of boring? It’s the mountain of boring coding syntax and dry practice problems you’re generally asked to work through before you can get to the good stuff — the stuff you actually want to do.

Nobody signs up to learn a programming language because they love syntax. Yet many learning resources, from textbooks to online courses, are written with the idea that students need to master all of the key areas of R syntax before they can do any real work with it.

That’s where new learners tend to drop off in droves. You get excited about learning a programming language because you want to do something with it, and but then you’re immediately led to this huge wall of complicated, boring stuff that’s between you and what you actually want to be doing. It’s no surprise that lots of students give up or drop off at points along their climb up this “cliff.”

There’s no way around learning syntax, in R or any other programming language. But there is a way to avoid the cliff of boring.

It’s a shame that so many students drop off at the cliff, because R is absolutely worth learning! In fact, R has some big advantages over other language for anyone who’s interested in learning data science:

  • The R tidyverse ecosystem makes all sorts of everyday data science tasks very straightforward.
  • Data visualization in R can be both simple and very powerful.
  • R was built to perform statistical computing.
  • The online R community is one of the friendliest and most inclusive of all programming communities.
  • The RStudio integrated development environment (IDE) is a powerful tool for programming with R because all of your code, results, and visualizations are together in one place. With RStudio Cloud you can program in R using RStudio using your web browser.

#learning and motivation #learn r #r #rstats #study

Jerad  Bailey

Jerad Bailey


Google Reveals "What is being Transferred” in Transfer Learning

Recently, researchers from Google proposed the solution of a very fundamental question in the machine learning community — What is being transferred in Transfer Learning? They explained various tools and analyses to address the fundamental question.

The ability to transfer the domain knowledge of one machine in which it is trained on to another where the data is usually scarce is one of the desired capabilities for machines. Researchers around the globe have been using transfer learning in various deep learning applications, including object detection, image classification, medical imaging tasks, among others.

#developers corner #learn transfer learning #machine learning #transfer learning #transfer learning methods #transfer learning resources