Last Updated: January 28, 2019

R is an open source programming language and software environment for statistical computing and graphics. R was created in 1992 and is supported by the R Foundation for Statistical Computing. R is widely used among statisticians and data miners for data analysis. The popularity of R has increased in the recent years. Here’s a list of the best R tutorials, best R books and best R courses to help you learn R programming language in 2019.

 

Best R courses & tutorials 2019

 

R Programming A-Z: R For Data Science With Real Exercises!

R Programming A-Z™: R For Data Science With Real Exercises! by Kirill Eremenko will teach you how to program in R at a good level. This R programming language tutorial will teach you R by doing. It assumes no programming or statistical background. This R programming language course is step-by-step and teaches you through live examples. You will learn how to use R Studio. You will practice working with statistical data, financial data and sports data in R. This is probably the best R programming language tutorials in 2019.

 

Data Science and Machine Learning Bootcamp with R

Data Science and Machine Learning Bootcamp with R by Jose Portilla will teach you how to use the R programming language for data science, machine learning, and data visualization. This R programming language tutorial is a comprehensive course that is almost 18 hours in length. It covers everything R programming related. You will learn how to use R to handle csv, excel, SQL files or web scraping. This R programming course will teach you how to use R for Data Science and Data Analysis. This R video course will teach you Machine Learning. Some of the Machine Learning topics you will learn include Linear Regression, K Nearest Neighbors, K Means Clustering, Decision Trees, Random Forests, etc. This is one of the best R and Data Science tutorials in 2019.

 

R Programming Hands-on Specialization for Data Science (Lv1)

R Programming Hands-on Specialization for Data Science (Lv1) by Irfan Elahi is an in-depth course on R language with real-world Data Science examples. This R Programming language tutorial will start from the very basics of introducing Data Science and the importance of R. You will start from setting up R development environment, R Data types, Data Structures (the building blocks of R scripts), Control Structures and Functions. This R programming language course will teach you how to work on Data Science Projects and Application development. You will use web technologies like HTML, Document Object Model, XPath and RSelenium in the context of web scraping to take your data analysis skills to the next level.  This R data Science tutorial will teach you everything you need to apply for Data Science jobs that make more money.

 

R Programming: Advanced Analytics In R For Data Science

R Programming: Advanced Analytics In R For Data Science by Kirill Eremenko will take your R & R studio skills to the next level. You require basic knowledge of R before taking this advanced R tutorial. This R programming language course will teach you all about data analytics, data science, statistical analysis in business, ggplot2, etc. You will learn how to perform data preparation in R. This R programming course will teach you how to perform the median imputation method in R. You will learn all about the Apply family of functions. This advanced R programming tutorial will teach you what lists are and how to use them. You will even learn how to work with date-times in R. This is the best advanced R programming language tutorial in 2019.

 

Cluster Analysis- Theory & workout using SAS and R

Cluster Analysis- Theory & workout using SAS and R by Gopal Prasad Malakar will teach you cluster analysis with SAS & R. You require basic knowledge of R, SAS and statistics. This Cluster Analysis with R tutorial will teach you all about the different type of cluster analysis. These include Hierarchical clustering and Non-hierarchical clustering (K means clustering). This R Cluster Analysis tutorial will help you learn R syntax for hierarchical and non hierarchical clustering. You will know the theory, business application, sas program and interpretation of output. This is the best R Cluster Analysis tutorial in 2019.

 

Best R books 2019

 

Bestsellers

SaleBestseller No. 1
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
  • O Reilly Media
  • Hadley Wickham, Garrett Grolemund
  • Publisher: O'Reilly Media
  • Edition no. 1 (01/05/2017)
  • Paperback: 522 pages
SaleBestseller No. 2
Modern Data Science with R (Chapman & Hall/CRC Texts in Statistical Science)
  • Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton
  • Publisher: Chapman and Hall/CRC
  • Edition no. 1 (02/02/2017)
  • Hardcover: 582 pages
SaleBestseller No. 3
Beginning Data Science in R: Data Analysis, Visualization, and Modelling for the Data Scientist
  • Thomas Mailund
  • Publisher: Apress
  • Edition no. 1 (03/13/2017)
  • Paperback: 384 pages
SaleBestseller No. 4
Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving (Chapman & Hall/CRC The R Series)
  • CRC Press
  • Deborah Nolan, Duncan Temple Lang
  • Publisher: Chapman and Hall/CRC
  • Edition no. 1 (04/23/2015)
  • Paperback: 539 pages
SaleBestseller No. 6
An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
  • An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years.
  • This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more.
  • Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.
  • Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
  • Publisher: Springer
SaleBestseller No. 7
Programming Skills for Data Science: Start Writing Code to Wrangle, Analyze, and Visualize Data with R (Addison-Wesley Data & Analytics Series)
  • Michael Freeman, Joel Ross
  • Publisher: Addison-Wesley Professional
  • Edition no. 1 (12/08/2018)
  • Paperback: 384 pages
SaleBestseller No. 8
R Graphics Cookbook: Practical Recipes for Visualizing Data
  • O Reilly Media
  • Winston Chang
  • Publisher: O'Reilly Media
  • Edition no. 1 (01/06/2013)
  • Paperback: 416 pages
SaleBestseller No. 9
Machine Learning and Data Science: An Introduction to Statistical Learning Methods with R
  • Daniel D. Gutierrez
  • Publisher: Technics Publications
  • Edition no. 0 (09/18/2015)
  • Paperback: 320 pages
Bestseller No. 10
The Book of R: A First Course in Programming and Statistics
  • Tilman M. Davies
  • No Starch Press
  • Kindle Edition
  • Edition no. 1 (07/16/2016)
  • English

R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

R for Data Science: Import, Tidy, Transform, Visualize, and Model Data by Hadley Wickham and Garrett Grolemund will help you learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. This is probably the best R programming language book in 2019.

 

R in Action: Data Analysis and Graphics with R

R in Action: Data Analysis and Graphics with R by Robert Kabacoff presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods. You’ll also master R’s extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on time series analysis, cluster analysis, and classification methodologies, including decision trees, random forests, and support vector machines.

 

The Art of R Programming: A Tour of Statistical Software Design

The Art of R Programming: A Tour of Statistical Software Design by Norman Matloff will take you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. This R programming book will help you create artful graphs to visualize complex data sets and functions. You will write more efficient code using parallel R and vectorization. This R book will help you learn how to interface R with C/C++ and Python for increased speed and functionality.

 

R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics


R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics by Paul Teetor helps you perform data analysis with R quickly and efficiently. This R programming language book contains a collection of concise, task-oriented recipes makes you productive with R immediately. The solutions provided range from basic tasks to input and output, general statistics, graphics, and linear regression. R Cookbook will help beginners get you started and make advanced developers better.

 

Advanced R


Advanced R by Hadley Wickham presents useful tools and techniques for attacking many types of R programming problems. This Advanced R programming language book develops the necessary skills to produce quality code that can be used in a variety of circumstances. You will learn the fundamentals of R, including standard data types and functions. This R book not only helps current R users become R programmers, it is also great for beginners. Intermediate R programmers can dive deeper into R and learn new strategies for solving problems. This is likely the best Advanced R programming langauge book in 2019.

 

Amazon Associates Disclosure: We are a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for us to earn fees by linking to Amazon.com and affiliated sites.

Last update on 2019-03-13 / Affiliate links / Images from Amazon Product Advertising API