As a beginner to R, I bought this book at the recommendation from Data Science for Fundraising: Build Data-Driven Solutions Using R and am so glad that I did. R4DS provides useful content to get started with R. The book consists of 5 main sections:
1. Getting started (Explore)
2. Data manipulation (Wrangle)
3. Scripting (Program)
4. Build models
5. Presenting information (Communicate)
Here’s a brief overview of each section:
Explore
I was a bit puzzled as the book jumps directly into plotting using the ggplot library. Although the authors are clear that the purpose of introducing ggplot is to keep our motivation high, seeing the ggplot syntax without a whole lot of background can be confusing at first. But then the authors do a great job at explaining the various aspects of ggplot. So my advice to other R beginners is to just keep going forward!
After the intro to ggplot, you learn about the basics of R, such as variables and functions, as well as intermediate topics such as writing scripts, manipulating data using dplyr, and lastly EDA. This section ends with a good overview of how to use RStudio to saves script files.
Wrangle
This section starts with an intro to tibbles, which is a new concept for handling data in R. This section is important since most of the functions in later chapters use tibbles, such as reading data from various sources. There are many important concepts that seem useful such as “tidying up” your data and cleaning data points (string and dates).
Program
This is a function section that introduces data pipes. This section explores how to chain complicated data operations together. You also get to see some good practice in writing human readable code. Then the book jumps into using the power of R as a functional programming language. Once I feel more proficient, I will take a deeper look at purr.
Model
Now, depending on your situation, you may not be interested in this section, which is focuses on predictive modeling. There are quite a few recipes that explore “why” questions. Definitely planning to come back to this chapter later.
Communicate
This section is useful because it introduces how to create reusablereports.
Overall, this is my go-to book along with the book I previously mentioned. This book is a solid reference book for learning R. Another good thing is that the companion website is regularly updated and you can copy and paste the code examples directly into RStudio. I’m looking forward to further exploring R and learning how to create my own data visualizations.
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Reviews with images
Good content, but print quality is so-so
To anyone who may be unaware, all of the contents of the book are available for free online and are updated regularly. I purchased this book in October 2019 and it was already out of date compared the the version online. However, not enough out of date to deter me from using it.I prefer to read books in print versus online, which is the main reason I purchased this book. It also allows me to study while on a plane, which is very convenient. The book is great, easy to understand, and provides a lot of questions and examples to work through in each chapter.I’m halfway through the book now, and one complaint that I have is that the quality of the print leaves a bit to be desired. If you look at my photos, you’ll see that I drew boxes around certain words/letters. I had to do this because the printed lines were SO faint that I completely missed it the first time I read it. This made the chapter more confusing than it should have been. I had to reread it a few times before I made out the super faint boxes. I compared it to the online version, which had the lines/boxes clearly drawn. I also wish the solutions to the practice questions and exercises were printed in the book so that I could check my answers. However, the answers are available online...it just adds a bit of unnecessary hassle. Those are really my only complaints so far.Overall, good book for beginner R and data science learners.
Top reviews from other countries
Joe Rat
“R for Data Science” is an exceptional book for Data Scientists.
Reviewed in Italy on September 11, 2022Diego Santiago Alarcon
Best way to learn data manipulation and creating graphs in R
Reviewed in Mexico on July 19, 2020Amin
Great book for R, RStudio, and learning about data
Reviewed in Canada on May 9, 2020