R is a perfect language for beginners who want to learn data analysis and visualization without getting lost in complex programming
Choosing the right beginner book can make your learning journey smoother. Whether you prefer hands-on projects or theory, the books listed here are great starting points.
The Book of R: A First Course in Programming and Statistics
Author: Tilman M. Davies
Description
This comprehensive guide offers a deeper, more traditional introduction to both the R language and the statistical concepts that underpin it, starting from absolute zero programming experience.
Why this book is recommended
Excellent for beginners who want a strong statistical foundation alongside programming. Very thorough, covering fundamental programming concepts like loops, variables, and functions in detail. Includes a vast number of hands-on exercises with downloadable solutions. Covers both basic graphics and contributed packages like ggplot2.
Hands-On Programming with R: Write Your Own Functions and Simulations
Author: Garrett Grolemund
Description
This book focuses specifically on building your core programming skills in R, teaching you how to write functions, organize code, and use control flow structures through engaging projects and simulations.
Why this book is recommended
A gentle introduction for those with no prior programming background. Strong emphasis on programming fundamentals rather than just data science tasks. Uses fun, simple projects to solidify learning (like dice roll simulations).
R in Action: Data Analysis and Graphics with R (3rd Edition)
Author: Robert I. Kabacoff
Description
This is a practical, task-oriented guide that walks you through using R for real-world data management, statistical analysis, and creating high-quality visualizations and reports.
Why this book is recommended
Provides a practical and informative guide to using R for analysis. Excellent coverage of statistical models and reporting, not just basic programming. Walks through key data manipulation, descriptive statistics, and visualization techniques. Well-regarded for its real-world applications and examples.
R for Data Science (2nd Edition)
Author: Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund
Description
This book provides a holistic and project-based introduction to data science using R, RStudio, and the modern set of tidyverse packages (like ggplot2, dplyr, and tidyr). It focuses on turning raw data into insight through a complete data science cycle.
Why this book is recommended
Teaches the most modern and efficient R data science practices. Covers the entire workflow: importing, cleaning, transforming, visualizing, and modeling data. The entire book content is available online for free. Written by the Chief Scientist at RStudio (Hadley Wickham) and other R experts.