R For Data Science: Import, Tidy, Transform, Visualize, And Model Data
  • R For Data Science: Import, Tidy, Transform, Visualize, And Model Data
  • R For Data Science: Import, Tidy, Transform, Visualize, And Model Data
  • R For Data Science: Import, Tidy, Transform, Visualize, And Model Data
ISBN: 1491910399
EAN13: 9781491910399
Language: English
Release Date: Jan 17, 2017
Pages: 522
Dimensions: 1.34" H x 8.98" L x 5.75" W
Weight: 1.63 lbs.
Format: Paperback
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R For Data Science: Import, Tidy, Transform, Visualize, And Model Data

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Book Overview

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.

Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way.

You'll learn how to:

  • Wrangle--transform your datasets into a form convenient for analysis
  • Program--learn powerful R tools for solving data problems with greater clarity and ease
  • Explore--examine your data, generate hypotheses, and quickly test them
  • Model--provide a low-dimensional summary that captures true signals in your dataset
  • Communicate--learn R Markdown for integrating prose, code, and results

Frequently Asked Questions About R For Data Science: Import, Tidy, Transform, Visualize, And Model Data

Book Reviews (6)

5
  |   6  reviews
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5
   One of the best books to learn R
This is one of the greatest books on programming written for the ever-expanding set of R and RStudio users. You learn by doing, by writing code. But there are some exercises that you have to do yourself and they aren't easy. The book is free on Amazon. com, and the rest is updated quite regularly. I have bought the book to support the writer. Trust me, all you have to do is to do all the exercises that you find in this book.
 
3
   Good content - Poorly Printed
The book is freely available on Amazon. com. I've always enjoyed reading from a book, even if I have to return it. The book is small, printed in small font, and bound tightly so that it won't stay open to a page. This made it a poor physical workbook in my hands _ especially as you try to type _ so I opted to continue to use the online version. It's great to be back home, Dad.
 
5
   Excellent primer for long time SAS user
Thanks to Gremlin, I got to realize how powerful that my old friend SAS is and how easy it is to use R to perform the same data manipulations. The book has brief chapters on each functional group, along with some illustrations. Not sure if the book would be as good for student or new comer who doesn't realize that tools like SAS and R are such necessary and powerful tools if they are not willing to climb steep learning curves to achieve the required end.
 
4
   The (current) best overview of the Tidyverse for data science
The main reason you would buy this book is to get introduced to the tidy way of doing data science in R—in particular, learning about the many packages the Tidyverse has to offer for data visualization, processing, string manipulation, and modeling. You could probably do equally well doing DataCamp courses on similar topics, so it's up to you to decide what's best for your learning style. Not for beginners. Even for programming newbies, Wickham assumes more comfort jumping into R than most. Ideal if you have some programming experience with any language and have seen a little bit of R already.
 
4
   Useful book for especially for data visualization
A useful book for data visualization. Both packages are excellent for students who need a good trunk of knowledge in ggplot2, tidyverse, and modelr packages. Dave is a great teacher and I would recommend it to anyone. Learning how to manipulate data is a huge and often underrated part of machine learning, and will be useful until data becomes useful again, said Dr. Samudram. Even with the introduction of a basic system, it won't likely ever be outdated, just updated. Data Visualization for Dummies by Robert B. Schaeffer does a good job of teaching data visualization. Not limited to ggplot2 and tidyverse, but certainly heavy on them.
 
5
   Best book to learn how to handle data in R
Thanks for the book. Note the subheading of this terrible parable in the "Persuasion" series, "Chapter Two: Two Lines of Violations of the Conciliation." Is a learning by doing book, Rowling said. Full color, two-tone papers are backed by 10-year warranties. The book will remain open, he said.
 
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