1.R Programming for Beginners: An Introduction to Learn R Programming with Tutorials and Hands-On Examples
This book is designed for beginners and those interested in learning programming, particularly R, a powerful language used in cutting-edge research like machine learning. The guide provides step-by-step instructions for setting up and installing the R environment, executing R scripts, understanding R syntax, writing first R scripts, and understanding the six data types supported by the R programming language. It also covers naming variables and assigning values, writing well-defined user functions, controlling program flow with decision-making control structures and loops, and visualizing data with R programming. The book is suitable for both beginners and experienced R programmers, providing everything they need to master R completely. The book is designed to help readers move beyond Excel sheets and excel in R programming.
Rated 4.3 on Amazon.
You can buy this book on Amazon.com.
2.The Book of R: A First Course in Programming and Statistics
The Book of R is a beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. It covers basic data handling, writing simple programs, and advanced topics like statistical summaries, tests, and modeling. The book also covers data visualizations using R’s graphics tools and packages, and interactive 3D visualizations using the rgl package. The book includes hands-on exercises and downloadable solutions, covering fundamental programming, statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, accessing R’s functions, libraries, and data sets, drawing valid conclusions from data, and creating publication-quality graphics of results. The book provides a solid understanding of statistics and R’s functionality, making it an essential tool for data analysis beginners.
Rated 4.6 on Amazon.
You can purchase this book here.
3.Hands-On Programming with R: Write Your Own Functions and Simulations
This book teaches readers how to program using the R language, enabling them to solve practical data science problems. It covers data loading, assembly, disassembly, navigation, function writing, and using R’s tools. The author, Garrett Grolemund, teaches more than just data visualization and modeling, demonstrating how to store, retrieve, and change data values in memory, write programs and simulations that outperform typical R users, use R programming tools like if else statements, for loops, and S3 classes, and learn to write fast vectorized R code.
Rated 4.4 on Goodreads.
The book is available here.
4.R for Data Analysis in easy steps: R Programming Essentials
The R programming language is widely used for data analysis, particularly in the context of the Internet of Things (IoT). This book, R for Data Analysis in easy steps, provides a step-by-step guide on how to create graphic visualizations from gathered data. The book explains the core programming principles of R, including storing data in vectors for simple graphs, creating matrices for better data manipulation, creating data frames from imported data sets, and employing the “Grammar of Graphics” for advanced visualizations. The book includes separate chapters on major features of the R programming language, complete example programs, and code for each script. The book is ideal for newcomers to computer programming, as it provides a sound understanding of R programming and allows readers to write their own scripts for data analysis. The book is free and downloadable for easy understanding.
Rated 4.3 on Amazon.
This book can be purchased here.
5.R in Action: Data Analysis and Graphics with R
R in Action, Second Edition is a comprehensive book that teaches users how to use the R language for data analysis. The book provides practical solutions, a crash course in statistics, and a crash course in dealing with messy and incomplete data. It also covers forecasting, data mining, and dynamic report writing. R is a powerful programming language for statistical computing, used by thousands of major corporations and institutions worldwide. The audiobook includes a complete R language tutorial, techniques for debugging programs, OOP in R, and over 160 graphs. Dr. Rob Kabacoff, a seasoned researcher and teacher, maintains the popular Quick-R website.
Rated 4.6 on Amazon.
This book can be purchased here.
6.The Art of R Programming: A Tour of Statistical Software Design
The Art of R Programming is a comprehensive guide to software development using R, covering basic data structures to advanced topics like closures, recursion, and anonymous functions. It covers functional and object-oriented programming, mathematical simulations, and data rearranging. The book covers creating graphs, writing efficient code, interacting R with C/C++ and Python, finding new packages for text analysis, image manipulation, and debugging techniques. It is suitable for various applications, including aircraft design, weather forecasting, and data management. No statistical knowledge is required, and programming skills can range from hobbyist to pro.
Rated 4.5 on Amazon.
This book is available here.
7.R for Data Science
R4DS is a book that teaches data science using R, covering various skills such as data structure, transformation, visualization, and modeling. It provides best practices for data science, such as cleaning data, drawing plots, and using graphics grammar, literate programming, and reproducible research. The book also teaches how to manage cognitive resources to facilitate discoveries during data exploration. The website is free to use and licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License. A physical copy can be ordered from Amazon. The book is also available for donation to Kākāpō Recovery, a critically endangered native NZ parrot. By contributing to R4DS, you agree to abide by its terms.
You can read this book here.
8.Learning R Programming
This book provides an in-depth exploration of the R language, a high-level functional language essential for data science and statistics. It offers hands-on examples and a comprehensive understanding of R’s data structures, processing techniques, and popular packages. The book covers basic functions, data structures, statistics, data mining, visualization, root solving, optimization, R’s evaluation model, object-oriented programming, relational and non-relational databases, high performance computing techniques, web scraping, and creating RMarkdown, an interactive app. The book aims to help beginners and those unfamiliar with R’s unique behaviors develop a broad and consistent understanding of the language. The book covers common tasks such as data analysis, databases, web scraping, high performance computing, and document writing. By the end of the book, the reader will be a confident R programmer adept at solving problems using the right techniques.
Rated 4.3 on Amazon.
You can purchase this book on Amazon.com.
Its like you read my mind You appear to know so much about this like you wrote the book in it or something I think that you can do with a few pics to drive the message home a little bit but instead of that this is excellent blog A fantastic read Ill certainly be back