Hands–On Programming with R: Write Your Own Functions and Simulations

Today my order for this book arrived, and I've had a couple of hours to pick it up and begin going through it.So far, I'm on p. 42 and have just started Part 2 of the book. Garrett Grolemund writes like a teacher talks. The points are well made, explained and situated in a scale appropriate context for a novice programmer.And there's the rub: Dr Grolemund approaches R in a way that is quite novel for me. He approaches it, and invites the reader to take the same perspective, as a programming language. Readers become apprentice programmers doing data science. His treatment of data objects, how they are combined in functions, replicated and plotted are very well discussed through the models of casino games.Through four game programmes, Dr Grolemund outlines a host of ways to understand and interact with the large and, for the novice acolyte, a complex, language that is R. Through the use of well documented reader-oriented exercises in programming functions and scripts to perform the mechanics of data analysis, Dr Grolemund gives as close-to-hands-on mode of instruction that I think one can offer. Congratulations to the author for good writing, and clear, tractable examples.But what is apparent underneath Dr Grolemund's writing is a way of approaching data sets. By crafting routines to handle data, to manipulate it, and to run it multiple times to obtain frequencies and trend patterns, the approach is to programme R and feed it data sets as arguments. This gives the novice the perspective of R as a language with which to express and test ideas using data.Admittedly, I haven't gotten that far into the book yet. These are early impressions, but let's say ... say far, very good!

I already knew many of the things presented, but the value of the book is not about learning functions or commands per se, but defining problems and working out how to solve them, first logically, and then using bread and butter R techniques like subsetting.The author has succeeded in making this an accessible book on learning R, by solving interesting case studies (gambling!) instead of being too abstract.I don't have any developer experience or training, so was very happy to see good explanations on programming aspects. Its certainly not common sense, but the discussions on R environments was completely new to me, yet seems fundamentally important, and explained why my attempts at writing functions never worked (because variables always seemed to remain unchanged).Also - kudos to the author, I had a question which I emailed to him, and he responded really quickly. It relates to a sister product so I'll copy an excerpt below:"You are right: R for Data Science *is* Data Science with R. The name changed after I wrote Hands-On Programming with R. I'm still writing R for Data Science and plan to complete it in July...""I recommend that you read Hands-On Programming with R before you read R for Data Science. I wrote it as a prerequisite for the second book (originally they were attached with Hands-On Programming for R as the first part)."

Just finished working through this and I have mixed feelings about. It's written in an easy going and chatty style, but in my opinion tries to do too much in such a small volume. Trying to explain closures and S3 classes in an introductory book is a bit too ambitious, especially as not much time is spent on either. This space would be better used describing the APPLY family, perhaps? Some simple R functionality is explained at great length then you seem to have these interludes where complex stuff is mentioned briefly. Not a classic of R programming books - I recommend A Book of R as a more comprehensive and coherent read.

As the title suggests this book adopts a hands-on approach to simulation programming in R. I found that so refreshing, thank goodness books like these are now becoming available for R. For months I had been watching tutorials on Youtube and reading technical tomes on simulation and on R. But none of these actually showed me what to do. This book will have you writing code on R within the first few pages. It really is the best way to learn. Great feeling of satisfaction when you complete each project. Packed with handy tips also. If, like me, you are a researcher looking for a way to get started using R as a tool, this book is the best thing I have discovered by far.

Excellent learning resource for people wanting to learn R and get their heads around the basics - only comment, P11, Fig 1-4: 1+1 does not = 1.

A good guide, the examples of card games help bring dull code to life

Terrible looy

As someone accustomed to programming in SAS, this book was very helpful to me for learning how to switch over to R. An easy to follow, well-written, step-by-step guide that covers a variety of useful topics.