A review of the book for research, educational and recommendations.

https://r4ds.had.co.nz/
R for Data Science. (Imag. Credit: O’Reilly).

Recommendation numbered Nº: 17022020p1


🔘 Book page

-Creative Commons address: r4ds.had.co.nz
-Paid version address: amzn.to/2PJ268i

📌 For your review and personal analysis, copy and paste the address of the book page in your browser. The educational and research community will also thank you for evaluating this information (above). The technical, ethical and labor implications of Artificial Intelligence (AI) will affect us all. And it is everyone’s responsibility.


Summary

“This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science. Just as a chemist learns how to clean test tubes and stock a lab, you’ll learn how to clean data and draw plots—and many other things besides. These are the skills that allow data science to happen, and here you will find the best practices for doing each of these things with R. You’ll learn how to use the grammar of graphics, literate programming, and reproducible research to save time. You’ll also learn how to manage cognitive resources to facilitate discoveries when wrangling, visualising, and exploring data”.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”. (Source: website book and Amazon).

Whenever you measure the same thing twice, you get two results—as long as you measure precisely enough. This phenomenon creates uncertainty and opportunity. Author Garrett Grolemund, Master Instructor at RStudio, shows you how data science can help you work with the uncertainty and capture the opportunities. You’ll learn about:

  • Data Wrangling—how to manipulate datasets to reveal new information.
  • Data Visualization—how to create graphs and other visualizations
  • Exploratory Data Analysis—how to find evidence of relationships in your measurements.
  • Modelling—how to derive insights and predictions from your data
  • Inference—how to avoid being fooled by data analyses that cannot provide foolproof results.

Authors

(Unofficial biography. For informational purposes only).

Garrett Grolemund is a statistician, teacher and R developer who currently works for RStudio. He sees data analysis as a largely untapped fountain of value for both industry and science. Garrett received his Ph.D at Rice University in Hadley Wickham’s lab, where his research traced the origins of data analysis as a cognitive process and identified how attentional and epistemological concerns guide every data analysis.

Hadley Wickham is an Assistant Professor and the Dobelman FamilyJunior Chair in Statistics at Rice University. He is an active memberof the R community, has written and contributed to over 30 R packages, and won the John Chambers Award for Statistical Computing for his work developing tools for data reshaping and visualization. His research focuses on how to make data analysis better, faster and easier, with a particular emphasis on the use of visualization to better understand data and models.


🔘 Book page

-Creative Commons address: r4ds.had.co.nz
-Paid version address: amzn.to/2PJ268i

📌 For your review and personal analysis, copy and paste the address of the book page in your browser. The educational and research community will also thank you for evaluating this information (above). The technical, ethical and labor implications of Artificial Intelligence (AI) will affect us all. And it is everyone’s responsibility.


Please, thank the authors and the Publisher

Thank you very much for this work to authors @hadleywickham, @StatGarrett and Publisher @OReillyMedia, via @States_AI_IA #R #datascience #free #ebook #ai #artificialintelligence #thebibleai #openscience #openaccess #thanks


Sheet book
Internal Id17022020p1
AuthorHadley Wickham, Garrett Grolemund
TitleR for Data Science
Book website1.- Creative Common Version: r4ds.had.co.nz
2.- Paid version: amzn.to/2PJ268i
Publisher (1) associated with ISBNOReilly
Book’s own website as an extra Publisher(2)r4ds.had.co.nz
Publication dateDecember 2016
Reviews on the book (if applicable)Amazon
Available for sale at (if applicable)Amazon
ISBN978-1491910399
ObservationsPages, 520
Access to the book page is provided by the Publisher herself (or the author). Keep in mind that the policy of the Publisher or the author may change. You must observe and comply with the terms of use set by the publication.Warning 1
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 🔘 Table of associated records

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R4Resource official title:R for Data Science
R5Publisher:OReilly
R6Resource website (1) ( #OpenAccess | #Openscience ): r4ds.had.co.nz
R7Resource website (2) (Editorial|company):oreilly.com/library/view/r-for-data/9781491910382/
R10ISBN13 (without “-“):9781491910382
R12Authors (separated by commas):Hadley Wickham, Garrett Grolemund
R14Keyword (selected 1 among the labels applied to this entry):=datascience
R15QR code (of the linked url at WP):La imagen tiene un atributo ALT vacío; su nombre de archivo es chart
R16Time stamp URL:web.archive.org/web/20200217085547/https://editorialia.com/2020/02/17/r-for-data-science/
R17Digital signature URL:Pending signature