R for data science

Contributor(s):

Material type: Text

TextLanguage: English Publication details: O'Reilly, 2016Edition: Fourth releaseDescription: 492 p. il. col. 23 cm.ISBN:

9781491910399

Subject(s):

Online resources:

Contents:

Includes index. Preface-- Part I. Explore-- Part II. Wrangle-- Part III. Program-- Part IV. Model-- Part V. Communicate--

Summary: 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. ;

Holdings ( 1 )
Title notes ( 2 )

Holdings
Item type	Current library	Call number	Status	Date due	Barcode
Book	TBS Barcelona Libre acceso	QA276.45.R3 WIC (Browse shelf(Opens below))	Available		B03695

Includes index. Preface-- Part I. Explore-- Part II. Wrangle-- Part III. Program-- Part IV. Model-- Part V. Communicate--

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. ;