Chapter 1 Preface

Meet the Author

Hello! My name is Wendy Huynh and I am a current PhD student working in the behavioral neurosciences. I began my R journey at the end of my first year of graduate school, slowly and painfully piecing together code. Although programming was never really part of my program, I now see it as an integral part of my work.

Many fellow graduate students expressed interest in learning R, but didn’t know where to begin. Programming with R is still relatively niche among my cohort and there are very few formal classes teaching this subject.

Although there are many amazing guides/textbooks for R out there, very few of them featured examples relevant for my specific needs and were user-friendly enough for a true beginner. In the Fall of my second year, I began teaching a new graduate student in my lab everything I knew about R. However, I quickly found that teaching R – even just to one person – was very time consuming. I decided to write up assignments as a “short” guide to R. After writing a short 11 page “first assignment” and receiving positive feedback, I began writing up a second assignment. Then a third. Soon enough, I had written enough pages that I couldn’t deny that this “short guide” had turned into a book. To this day, I am continually learning new techniques for managing my data in R and teaching what I know to anyone who wants to learn. I strongly believe that learning efficient techniques in handling data is crucial in graduate school. Teaching R is something I genuinely enjoy doing and I hope you find this book to be useful on your R journey.


I would like to thank my colleague and friend, Andrea (Andi), for convincing me to write this book and providing lots of guidance for the kinds of content to include. I’d also like to thank my partner Matt for his endless support and patience, as well as my mentors, Scott and Rick, both of whom nudged me to learn R in the first place. I feel so fortunate and privileged to have the amazing support system and mentorship through my journey in graduate school and sincerely hope that everyone experiences this excitement and gratitude in their lives.

Packages Utilized

There are so many amazing resources and people who paved the way for me. Without these brilliant people, I would still be wrangling my data using slow, error-prone techniques. Here is a list of authors who developed the packages used in this book (in order of package name): Xie (2015), Singmann et al. (2019), R Core Team (2019), Xie (2019a), Wickham, François, et al. (2019), Lenth (2019), Wickham (2019a), Wickham, Chang, et al. (2019), Arnold (2019), Zhu (2019), Xie (2019b), Bates et al. (2019), Bates and Maechler (2019), Henry and Wickham (2019), Wickham, Hester, and Francois (2018), Wickham and Bryan (2019), Allaire et al. (2019), Wickham (2019b), Müller and Wickham (2019), Wickham and Henry (2019), Wickham (2017), and Ooms (2018).


Allaire, JJ, Yihui Xie, Jonathan McPherson, Javier Luraschi, Kevin Ushey, Aron Atkins, Hadley Wickham, Joe Cheng, Winston Chang, and Richard Iannone. 2019. Rmarkdown: Dynamic Documents for R.

Arnold, Jeffrey B. 2019. Ggthemes: Extra Themes, Scales and Geoms for ’Ggplot2’.

Bates, Douglas, and Martin Maechler. 2019. Matrix: Sparse and Dense Matrix Classes and Methods.

Bates, Douglas, Martin Maechler, Ben Bolker, and Steven Walker. 2019. Lme4: Linear Mixed-Effects Models Using ’Eigen’ and S4.

Henry, Lionel, and Hadley Wickham. 2019. Purrr: Functional Programming Tools.

Lenth, Russell. 2019. Emmeans: Estimated Marginal Means, Aka Least-Squares Means.

Müller, Kirill, and Hadley Wickham. 2019. Tibble: Simple Data Frames.

Ooms, Jeroen. 2018. Writexl: Export Data Frames to Excel ’Xlsx’ Format.

R Core Team. 2019. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing.

Singmann, Henrik, Ben Bolker, Jake Westfall, Frederik Aust, and Mattan S. Ben-Shachar. 2019. Afex: Analysis of Factorial Experiments.

Wickham, Hadley. 2017. Tidyverse: Easily Install and Load the ’Tidyverse’.

Wickham, Hadley. 2019a. Forcats: Tools for Working with Categorical Variables (Factors).

Wickham, Hadley. 2019b. Stringr: Simple, Consistent Wrappers for Common String Operations.

Wickham, Hadley, and Jennifer Bryan. 2019. Readxl: Read Excel Files.

Wickham, Hadley, Winston Chang, Lionel Henry, Thomas Lin Pedersen, Kohske Takahashi, Claus Wilke, Kara Woo, and Hiroaki Yutani. 2019. Ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics.

Wickham, Hadley, Romain François, Lionel Henry, and Kirill Müller. 2019. Dplyr: A Grammar of Data Manipulation.

Wickham, Hadley, and Lionel Henry. 2019. Tidyr: Easily Tidy Data with ’Spread()’ and ’Gather()’ Functions.

Wickham, Hadley, Jim Hester, and Romain Francois. 2018. Readr: Read Rectangular Text Data.

Xie, Yihui. 2015. Dynamic Documents with R and Knitr. 2nd ed. Boca Raton, Florida: Chapman; Hall/CRC.

Xie, Yihui. 2019a. Bookdown: Authoring Books and Technical Documents with R Markdown.

Xie, Yihui. 2019b. Knitr: A General-Purpose Package for Dynamic Report Generation in R.

Zhu, Hao. 2019. KableExtra: Construct Complex Table with ’Kable’ and Pipe Syntax.