R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

great for beginners

As usual from Wickham, book is excellent--very well written and very helpful.

This is a great reference guide for using R for basic (and some more advanced) data science tasks. It does a good job of capturing the basics and directing you to additional resources as needed.

The content detail, coupled with the understandability of the information being presented, makes this an incredibly valuable foundational textbook!! Bayesian concepts had been a little confusing and hard to inculcate but this book presented these essential concepts in a way that made it easy to grasp. This is a must have book for anyone looking to learn or deepen their understanding in Bayesian statistics.

Well written, covers a breadth of useful topics. Highly recommend if you use R already and want to learn more.

I used this for a data science course. A lot of great information and really helps when learning ggplot2.

I used this excellent resource in conjunction with my Google Data Analytics course!

Three stars is a compromise between five stars and just one.Five stars because this book covers what it covers, data manipulation and graphing, extremely well.One star, because it doesn’t cover what it says on the cover. The subtitle is “Import, Tidy, Transform, Visualize, and Model Data” and yet there are no modelling topics to be found in the table of contents or index – not even something as basic as a linear regression. Indeed, on page 164 the authors state “We're not discussing modelling in this book because understanding what models are and how they work is easiest once you have tools for data wrangling and programming in hand.” I haven’t read the whole text, yet, but I’ll take that at face value.So, the subtitle says modelling, and there is no modelling. Not everyone will agree with me, but I’d go further and suggest that, without modelling, you are not even really doing data science. The book should have been called “Data wrangling with R” or something like that. The existing main title is misleading, and the subtitle is indefensible false advertising.