Learning R

Learning R is an introductory R tutorial by data scientist Richard Cotton, written for readers with no programming background. The Chinese edition was translated by Liu Jun and published by Posts & Telecom Press as part of its Turing Programming Series. The book is divided into three parts. Part One, "The R Language," explains data types and programming concepts chapter by chapter, from installing R and choosing an IDE and using R as a scientific calculator, to inspecting variables and the workspace, vectors, matrices and arrays, lists and data frames, environments and functions, strings and factors, flow control and loops, advanced loops, installing and using packages, and working with dates and times. Part Two, "The R Workflow," moves into practice, linking the standard workflow end to end: getting data, cleaning and transforming data, exploring and visualizing, distributions and modeling, programming, and building packages. Part Three consists of appendices covering attributes of variables, other things R can do, and answers to the questions and exercises in each chapter. Every chapter includes quizzes and hands-on exercises that require writing R code, helping readers consolidate what they learn as they type. The author has long worked in data science and has developed R packages such as assertive and sig; the explanations stay close to real-world usage, making the book suitable as a first book for systematically self-studying R and data analysis.