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R for data science : Import, Tidy, Transform, Visualize, And Model Data Paperback – 20 Jan 2017

4.4 out of 5 stars 15 customer reviews

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Product description

Book Description

Visualize, Model, Transform, Tidy, and Import Data

About the Author

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.

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.


From the Publisher

Data Science for Business Data Science from Scratch Doing Data Science R for Data Science Data Science at the Command Line Python Data Science Handbook
What you need to know about data mining and data-analytic thinking First principles with python Straight talk from the frontline Visualize, model, transform, tidy, and import data Facing the future with time-tested tools Tools and techniques for developers
Pages 414 330 408 250 212 500

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Product details

  • Paperback: 522 pages
  • Publisher: O′Reilly; 1 edition (20 January 2017)
  • Language: English
  • ISBN-10: 1491910399
  • ISBN-13: 978-1491910399
  • Product Dimensions: 15.2 x 2.7 x 22.9 cm
  • Average Customer Review: 4.4 out of 5 stars 15 customer reviews
  • Amazon Bestsellers Rank: #93,900 in Books (See Top 100 in Books)
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