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

This is our course text. Recommended by our instructor.

Its a nice book written in simple language

Easy to read and understand the concepts

It's the best book for data wrangling and data visualization in R, even for intermediate R coders. You are bound to learn new details in most chapters, even if you think you don't. The cover of this book is misleading: do not expect this book to be about modeling. The authors explicitly mention in the introduction that modeling in R is left for another book. I suppose the book designers at O'Reilly didn't bother reading the book itself. The code samples in this book are of very good quality and are printed in color. The text itself reads nicely. The exercises are sometimes challenging but always doable.

If you're looking for a book on data analytics using R, this is the one. Stop looking.

Con base a mi experiencia considero que es un excelente libro para adentrarte en el mundo de la programación bastante bien explicado y con ejemplos bastante sencillos. Si ya tienes experiencia programando considero que también es una excelente herramienta para comprender de manera fácil el Tidyverse.

asi de simple, es el mejor. Practico y desde la hoja 1 aprendes.

I started doing data science in my job in 2017 and was lucky to learn it based on the great first edition of "Data science with R" by Hadley Wickham. Since then, I spent countless hours working on different data science projects. My learning of course continued, mostly through online documentations, blog articles and I delved into more advanced topics like modellig, shiny and deep learning with other books. I also started coding in python from time to time. When the second edition of "R for data science" came out last year, I immediately ordered the book but it lay inside my shelf for some time. Recently, I felt I want to work myself through the second edition because I felt a bit overwhelmed with all the different data science topics out there and wanted to do a "2024 wrap up" of the tidyverse for myself. Halfway through the second edition now and so far this has been very rewarding! Even though I consider myself an advanced R user, I still learn a lot. Because a lot has happened in the tidyverse in the last 7 years and the book summarizes the current "best practices" perfectly. The style of writing makes it very interesting! When I have time on a free day, I love to sit in the morning with a cup of coffee to work myself through the pages and from time to time I get an aha moment like: "Oh nice I didnt know function XX has an argument to do YY now. That makes my life easier!". Still, the book is straightforward for beginners too. In my opinion a much easier and complete overview to get started with data science compared to anything else out there in Python. To summarize: Being a newcomer or long-term data scientist, this book is for everyone!