Preface

This short book was prepared as supplementary material for the R for Data Science course I taught at the University of Notre Dame in the spring of 2019. This class aims to equip students with basic knowledge of R in data manipulation and data visualization for social and behavioral research. The first part of the class will introduce the very basics of R including the types of data such as vectors, matrices, and data frames. The second part of the class will introduce data manipulation and preprocessing methods such as data transformation, subsetting, and combination. The third part will deal with specific types of data such as strings, texts, dates and times, images, audios, and videos. The fourth part will teach ggplot2 and related packages for data visualization. The last part of the class will illustrate how to conduct data analysis using the above techniques through case studies such as text mining and log analysis.

I would like to thank all the students who took the class and motivated the preparation of the document.

I will keep improving the document. If you have any comments or suggestions, please contact me at Zhiyong Zhang, 390 Corbett Family Hall, University of Notre Dame, IN 46530. You can drop me an email at zhiyongzhang(at)nd.edu.

Contents

The current version of the book [2019-04-08] consists of the following chapters.

Chapter 1. Introduction to the basics of R

Chapter 2. R programming

Chapter 3. Data manipulation

Chapter 4. String and text data

Chapter 5. Image data

Chapter 6. Audio data

Chapter 7. Video data

Chapter 8. Big data in R

Chapter 9. Data visualization

Chapter 10. Case study: Market basket analysis

Chapter 11. Case study: Log analysis

To cite the book, please use the following:

Zhang, Z. (2019). Practical Data Processing for Social and Behavioral Research Using R. Retrievable from https://books.psychstat.org/rdata.