R programming is about 70% widely used tool from among all the Data analytics tools and languages because it is an open source free software easily extendable with lots of packages.

Due to these reasons R Programming is an important skill acquired in the Data Science field of study.

Importance of R cannot be limited in words, so here we tried to consolidate the resources to learning R. Here you will find lists of Books, MOOCs ,tutorials and much more to learn R.

**Books**

There are lot of books has written on R. R is worthwhile in variety of fields(Data Science, Business Analytics, Social media and so on) , so here I tried to categorized books for R according to different usability of R.

##### 1.Books for Beginners

Beginning R – Free Download eBook – pdf

This book examines R language using simple statistical examples, showing how R operates in a user-friendly context. This book is useful for learning simple summary statistics , hypothesis testing, creating Graph, regression , and much more . It covers formula notation, complex statistics, manipulating data and extracting components and rudimentary programming.

With this book, you’ll learn how to load data, assemble and disassemble data objects, navigate R’s environment system, write your own functions and use all of R’s programming tools.

RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modelling data.

##### 2.Installing RStudio

This concise book provides new and experienced users with an overview of R Studio, as well as hands-on instructions for analysing data, generating reports, and developing R software packages.

##### 3.Work with Graphics and R

This Practical guide provides more than 150 recipes to help you generate high-quality graphs quickly, without having much knowledge of R’s graphics systems.

Guidebook to R Graphics Using Microsoft Windows

This book takes readers step by step through the process of creating histograms, oxplots ,strip charts ,time series graphs , steam-and-leaf displays , scatterplot matrices and map graphs.

##### 4.Data visualization using R and Java script

Pro Data Visualization using R and JavaScript

In this book, you will learn how to gather data effectively, and also how to understand the philosophy and implementation of each type of chart, so as to be able to represent the results visually.

##### 5.Data science algorithms implemention in R

Practical Data Science Cookbook

This books guide you from the basics( how to set up your numerical programming environment) to advance level of data science pipeline( introduce you to data science iterative process of project completion).After leraning this book will able to implement data science algorithms in both R and Python.

##### 6.Machine learning algorithms with R

If you are an experienced programmer interested in crunching data this book will get you started with machine learning – a toolkit of algorithms that enables computers to train themselves to automate useful tasks.

Using R programming, you will learn how to analyze sample dataset and write simple codes for machine learning algorithms. Machine learning for hackers is ideal for programmers from any background, including business, government, and academics research.

Machine Learning with R Cookbook

This book covers the basics of R by setting up a user-friendly programming environment and performing data ETL in You will then dive into important machine learning topics including data classification, regression, clustering, association rule mining, and dimension reduction.

##### 7.Social media analysis with R

This book provides detailed instructions on how to obtain, process and analyze a variety of socially-generated data while providing a theoretical back ground to help you accurately interpret your findings.

##### 8.Business analytics and R

Data Mining and Business Analytics with R

In This book readers are provided with the needed guidance to model and interpret complicated data and become adept at building powerful models for prediction and classification.

##### 9.Web** development in R**

Web Application Development with R Using Shiny

After learning this full book , you will be able to build useful and engaging web applications with only a few lines of code- no java script required.

##### 10.Analysing Big Data: R and Hadoop

Big Data Analytics with R and Hadoop

This book is focused on the techniques of integrating R and Hadoop by various tools such as RHIPE and RHadoop.

**Tutorials**

Codeschool started teaching programming language in the banner of ‘Learn with doing it’. It is an interactive course and the content presentation is very lucid.

2.DataCamp: The Easy Way To Learn R & Data Science Online

Datacamp is the best portal to learn about data science. They’ve created tutorials in simple manner.

3.R Tutorial at tutorialspoint

Tutorialspoint ,One of the site widely known for sharing knowledge about various programming languages. They have created R tutorials as well.

**MOOC’s**

Here is list of different MOOC program where you can learn R

- R Programming – Johns Hopkins University | Coursera
- Introduction to R for Data Science
- Free Introduction to R Programming Online Course| DataCamp
- R Programming A-Z™: R For Data Science With Real Exercises!
- Learn R Programming from Scratch – Udemy
- Introduction to R for Data Science| edX
- R Programming – Johns Hopkins University | Coursera
- R Fundamentals | Dataquest.io
- swirl: Learn R, in R.