R for Everyone: Advanced Analytics and Graphics (Addison-Wesley Data & Analytics Series)

This is the 2nd R book I have purchased. The first one was Programming Skills for Data Science by M Freeman and J Ross. Programming Skills was excellent to get started with R and R for Everyone was a comprehensive book aimed at intermediate to advanced programmers IMO. R for Everyone could also be used as a single textbook for an R class.Programming Skills for Data Science is a much better "intro" to R in my opinion for both non-programmers and experienced software practitioners. I had to skim much of R for Everyone initially but it will be the most useful as I gain experience and begin using the language at work.The R language reminds me of FORTRAN, which I took in college and was specialized for finance. Much of the standard library is built for EDA, data munging, and advanced graphics. Supposedly slower, these base functions can be used for creating stubs while learning to use the more flexible packages created by the R community.

After working with R for ~5 years I've read dozens of books on R, data science and machine learning. Unfortunately, I didn't know about R for Everyone when I started using R which would have been great. Even though I knew a lot about R after those 5 years, this book was really helpful. There were many things that I didn't understand perfectly but this book explained really well.And what is great about R for Everyone is that it both teaches you base R and tidyverse. It has a fantastic chapters on statistics and machine learning. After learning about R programming, tidyverse, statistics and machine learning in R it will teach you how to use RMarkdown, Shiny and shinydashboards.I would say this is a must read for anyone beginning using R or someone who's been using R for several years.

It is a pretty good book for beginners. I wanted something more advanced.

This should be a standard for teaching programming to non CS majors. It starts off slow and breaks down concepts into easily digestible pieces.

This book combines the right balance of math, science, and practical ways to go about and communicate the expectations for research projects. The "Foundations for Your Research" section has been invaluable in helping me explain to our analysts what they should expect to prepare when they start a project. The examples and step by step instructions are super easy to follow. We're planning on using this text as one of our foundational references for our fledgling R users group here at work.

I valued the step by step instructions. It was great tool for the SOA predictive analytics exam. I would highly recommend this book to anyone wanting or needing to learn R.

I bought this book “new” and it is obviously not new. It looks used

Well laid out and gives a good introduction to R - followed along while testing some programs and worked great for me!