Overview

Learn how to use R to turn data into insight, knowledge, and understanding. Ideal for current and aspiring data scientists, this book introduces you to doing data science with R and RStudio, as well as the tidyverse-a collection of R packages designed to work together to make data science fast, fluent, and fun. Even if you have no programming experience, this updated edition will have you doing data science quickly.You'll learn how to import, transform, and visualize your data and communicate the results. And you'll get a complete, big-picture understanding of the data science cycle and the basic tools you need to manage the details. Each section in this edition includes exercises to help you practice what you've learned along the way.Updated for the latest tidyverse best practices, new chapters dive deeper into visualization and data wrangling, show you how to get data from spreadsheets, databases, and websites, and help you make the most of new programming tools.You'll learn how to:Visualize-create plots for data exploration and communication of resultsTransform-discover types of variables and the tools you can use to work with themImport-get data into R and in a form convenient for analysisProgram-learn R tools for solving data problems with greater clarity and easeCommunicate-integrate prose, code, and results with Quarto

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9781492097402

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Hadley Wickham is Chief Scientist at RStudio and a member of the R Foundation. He builds tools (both computational and cognitive) that make data science easier, faster, and more fun. His work includes packages for data science (ggplot2, dplyr, tidyr), data ingest (readr, readxl, haven), and principled software development (roxygen2, testthat, devtools). He is also a writer, educator, and frequent speaker promoting the use of R for data science. Learn more on his homepage, http: //hadley.nz. Mine Çetinkaya-Rundel is Professor of the Practice and the Director of Undergraduate Studies at the Department of Statistical Science and an affiliated faculty in the Computational Media, Arts, and Cultures program at Duke University as well as Educator at RStudio. Mine works on innovation in statistics and data science pedagogy, with an emphasis on computing, reproducible research, student-centered learning, and open-source education. At RStudio, Mine's work focuses primarily on education for open-source R packages as well as building resources and tools for educators teaching statistics and data science with R and RStudio. Mine has authored four undergraduate statistics textbooks as part of the OpenIntro projects, teaches the popular MOOC Statistics with R on Coursera and is the developer and maintainer of Data Science in a Box. Mine is a Fellow of the ASA and an Elected Member of the ISI as well as the recipient of the 2021 Robert V. Hogg Award For Excellence in Teaching Introductory Statistics, the 2018 Harvard Pickard Award, and the 2016 ASA Waller Education Award. Garrett Grolemund is the author of Hands-On Programming with R and co-author of R for Data Science and R Markdown: The Definitive Guide. He is Director of Learning at RStudio and holds a Ph.D. in Statistics, but specializes in teaching. He's taught people how to use R at over 50 government agencies, small businesses, and multi-billion dollar global companies; and he's designed RStudio's training materials for R, Shiny, R Markdown and more. Garrett wrote the popular lubridate package for dates and times in R and creates the RStudio cheat sheets.

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