R is a popular programming language and is widely used in data science and statistics. In fact, it was designed for these particular fields. The popularity of data science has been increasing significantly over the past few years, which makes learning R an essential skill. This article lists the top R programming books one should read in 2024 to stay updated with the latest trends.

The Book of R: A First Course in Programming and Statistics

This book is a beginner-friendly guide to R, which can be read even by those without prior experience with the language. The book starts with the basics and covers concepts like performing statistical tests and modeling. It also consists of numerous exercises to help augment the reader’s knowledge.

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

“The Art of R Programming” focuses primarily on software development using R. However, one does not need to be an expert to get started with this book. It covers topics like object-oriented programming, running mathematical simulations, and using parallel R and vectorization to write more efficient code.

Hands-On Programming with R: Write Your Own Functions and Simulations

This book teaches how to solve data science problems using the R programming language. It also includes three practical data analysis projects, along with various examples that help readers understand the language’s fundamentals.

R All-in-One For Dummies

“R All-in-One For Dummies” consists of five mini-books that provide a comprehensive understanding of the language. The book also sheds light on the different types of projects and applications that R programmers generally tackle. This book is a good resource for beginners wanting to move into the data space.

R in a Nutshell

The author explains the numerous tasks one can achieve using R. The book covers how to write R functions and packages to prepare, visualize, and analyze data. The book consists of various real-world examples to simplify the learning.

Advanced R

This book explains how R works at the fundamental level. It is suitable for more advanced readers and provides a comprehensive coverage of object-oriented programming and metaprogramming.

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

The book provides more than 250 practical examples to teach how to perform data analysis quickly and efficiently using R. It covers topics like how to simplify data input and output, and how to build statistical models with linear regressions and analysis of variance.

The R Book

This book delivers a complete walkthrough of the R language and is well-suited for beginners. The book consists of numerous worked examples and provides an in-depth examination of essential R packages.

Data Wrangling with R

This book provides a guide on how to utilize the different R packages for loading, exploring, transforming, and visualizing data. The book provides information on various state-of-the-art libraries for data wrangling and how to work with different data types.

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

This is a beginner-friendly book that teaches how to import, transform, and visualize the data. It provides a comprehensive understanding of the different tools required to manage the data science cycle.

R Graphics Cookbook

“R Graphics Cookbook” helps programmers, data analysts, etc., to generate high-quality graphs quickly using R. The book consists of more than 150 practical recipes that facilitate more efficient data visualization. The book covers topics like histograms, density curves, box plots, network graphs, heat maps, and 3D scatter plots.

Efficient R Programming

This is a beginner-friendly book that covers how to write efficient R code. The book provides various techniques to write better code and also teaches how to determine the hardware capabilities for handling R computation.

R in Action

“R in Action” teaches how to perform statistical analysis using R and its packages. The book includes real-world challenges and covers topics like forecasting, data mining, and dynamic report writing.

R Packages: Organize, Test, Document, and Share Your Code

The book talks about the key components of an R package and teaches how to streamline the development process with devtools and the RStudio IDE. It also touches on topics like creating user-friendly websites with pkgdown.

R for Excel Users

This book introduces how to use R to import, modify, and summarize data sets in Excel. The book is written in simple language and can even be read by beginners.

Practical Data Science with R

This book explains the fundamentals of data science using various real-world examples. The book has numerous task-based tutorials based on R that equip its readers to tackle day-to-day data analysis and machine learning tasks efficiently.

Tidy Modeling with R: A Framework for Modeling in the Tidyverse

This book teaches how to create models using the tidyverse package of R. The book covers topics like building a model, tuning it for optimal results, and using statistical methods to compare, evaluate, and choose among models.

Mastering Shiny

“Mastering Shiny” covers building interactive apps, reports, and dashboards using R. The book provides various code samples and example apps to simplify the learning process and sheds light on how to ensure the optimal performance of Shiny apps in production.

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