R for Data Science: Import, Tidy, Transform, Visualize, and Model Data 1st Edition

4.7 out of 5 stars 428 ratings
ISBN-13: 978-1491910399
ISBN-10: 1491910399
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Editorial Reviews

About the Author

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.

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.

Garrett is passionate about helping people avoid the frustration and unnecessary learning he went through while mastering data analysis. Even before he finished his dissertation, he started teaching corporate training in R and data analysis for Revolutions Analytics. He's taught at Google, eBay, Axciom and many other companies, and is currently developing a training curriculum for RStudio that will make useful know-how even more accessible.

Outside of teaching, Garrett spends time doing clinical trials research, legal research, and financial analysis. He also develops R software, he's co-authored the lubridate R package--which provides methods to parse, manipulate, and do arithmetic with date-times--and wrote the ggsubplot package, which extends the ggplot2 package.


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4.7 out of 5 stars
4.7 out of 5
428 customer ratings
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Reviewed in the United States on October 14, 2017
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Top international reviews

ZigZag
5.0 out of 5 stars I have bought other books on R and Python programming which I found boring and very dry
Reviewed in the United Kingdom on March 6, 2018
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Chris
5.0 out of 5 stars I've found this book an excellent resource for taking a step back to fill in ...
Reviewed in the United Kingdom on March 20, 2017
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Chris
5.0 out of 5 stars Written by the master himself, it's a no-brainer.
Reviewed in the United Kingdom on December 11, 2017
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Elantair
5.0 out of 5 stars Must-have for data scientists
Reviewed in the United Kingdom on January 12, 2020
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snflower
4.0 out of 5 stars Good practical book
Reviewed in the United Kingdom on May 10, 2020
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Darek
5.0 out of 5 stars Good book
Reviewed in the United Kingdom on January 10, 2018
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Asir Ajmal
5.0 out of 5 stars A user friendly guide to R
Reviewed in the United Kingdom on August 8, 2019
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dengmw
5.0 out of 5 stars Easy to follow
Reviewed in the United Kingdom on March 10, 2019
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Shopaholic
3.0 out of 5 stars Confusing
Reviewed in the United Kingdom on May 22, 2019
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MP
5.0 out of 5 stars Fantastic book on R and data analysis in general
Reviewed in the United Kingdom on December 15, 2018
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Fernanda Valerio
5.0 out of 5 stars handy for a beginner
Reviewed in the United Kingdom on April 1, 2020
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GD
5.0 out of 5 stars If R is Ferrari of Data science world then this book is Nut and Bolt manual to cary out routine but critical operations on data
Reviewed in India on April 7, 2018
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Calioril
5.0 out of 5 stars R
Reviewed in the United Kingdom on April 2, 2018
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Andre veiga
5.0 out of 5 stars Probably the best book to get started with R
Reviewed in the United Kingdom on November 3, 2018
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Jeremy
5.0 out of 5 stars Great bok
Reviewed in the United Kingdom on August 18, 2019
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