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

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

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About the Book

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. Youll 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 youve learned along the way.

Youll 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.

About the Author

Hadley Wickham

Hadley Wickham is an Assistant Professor and the Dobelman FamilyJunior Chair in Statistics at Rice University. He is an active member of 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 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 Wickhams 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. Hes 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, hes 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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Product Details
  • ISBN-13: 9789352134977
  • Publisher: Shroff/o'reilly
  • Binding: Paperback
  • Language: English
  • Weight: 0 gr
  • ISBN-10: 9352134974
  • Publisher Date: 2017
  • Height: 24 mm
  • No of Pages: 520
  • Width: 229 mm

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