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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

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

  • Title R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
  • Author(s) Hadley Wickham  
  • Publisher:  O’Reilly Media; 1st edition (January 17, 2017)
  • Paperback: 520 pages
  • Language: English
  • ISBN-10 ‏ : ‎ 1491910399
  • ISBN-13 ‏ : ‎ 978-1491910399

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

Download R for Data Science: Import, Tidy, Transform, Visualize, and Model Data Language pdf – Learn how to use R to transform raw data into knowledge, understanding, and insight. This book introduces you to R, RStudio, and the tidyverse, a set of R tools that work together to make data research simple, fluent, and enjoyable. R for Data Science is meant to get you practicing data science as quickly as possible, even if you have no prior programming expertise.

Hadley Wickham and Garrett Grolemund, the authors, walk you through the process of importing, wrangling, examining, modeling, and communicating your data. You’ll gain a comprehensive grasp of the data science cycle, as well as the fundamental tools you’ll need to manage the details.

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Wickham and Grolemund have written a fantastic book that will guide a novice R user through the process of explanatory analysis. The “hadleyverse,” a collection of packages (ggplot2 for visualization, tidyr for reshaping, dplyr for selecting and filtering, purrr for functional programming, broom for linear models, and so on) that dramatically speed up most of the common steps involved in analysis, is used in their approach. Wickham’s work in these packages has resulted in a consistent concept that underpins them. Learning this mindset can be challenging at times, but the long-term advantages are great.

The book is divided into several sections that help you learn how to ingest, process, visualise, and model datasets. An online version of a large chunk of the book is available to give you a flavour of how it is written. Many people have been following it since it was first published. I’ve given copies of the book to a number of coworkers who are just getting started, and the feedback has been overwhelmingly good. I was already familiar with some of these packages, such as ggplot2, dplyr, and tidyr, but the book taught me purrr and how to effectively combine them.

About the Author

Hadley Wickham is a Rice University Assistant Professor and the Dobelman Family Junior Chair in Statistics. He’s a member of the R community who’s authored and contributed to over 30 R packages, and he won the John Chambers Award for Statistical Computing for his work on data reshaping and visualization tools. His research focuses on how to improve, speed up, and simplify data analysis, with a special focus on the use of visualization to better comprehend data and models.

Garrett Grolemund works at RStudio as a statistician, teacher, and R developer. Data analysis, he believes, is a largely untapped source of value for both industry and science.

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