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R Visualizations
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R Visualizations : Derive Meaning from Data

Book Details

Format Hardback or Cased Book
ISBN-10 1138599638
ISBN-13 9781138599635
Publisher Taylor & Francis Ltd
Imprint CRC Press
Country of Manufacture GB
Country of Publication GB
Publication Date May 12th, 2020
Print length 250 Pages
Weight 834 grams
Ksh 15,650.00
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This book is focused on one of the two major topics of doing data analysis: data visualization, aka, computer graphics. In one place the major R systems for visualization are discussed, organized by topic and not by system. Anyone doing data analysis will be shown how to use R to generate basic visualizations with any of R visualization systems.

R Visualizations: Derive Meaning from Data focuses on one of the two major topics of data analytics: data visualization, a.k.a., computer graphics. In the book, major R systems for visualization are discussed, organized by topic and not by system. Anyone doing data analysis will be shown how to use R to generate any of the basic visualizations with the R visualization systems. Further, this book introduces the author’s lessR system, which always can accomplish a visualization with less coding than the use of other systems, sometimes dramatically so, and also provides accompanying statistical analyses.

Key Features

  • Presents thorough coverage of the leading R visualization system, ggplot2.
  • Gives specific guidance on using base R graphics to attain visualizations of the same quality as those provided by ggplot2.
  • Shows how to create a wide range of data visualizations: distributions of categorical and continuous variables, many types of scatterplots including with a third variable, time series, and maps.

  • Inclusion of the various approaches to R graphics organized by topic instead of by system.
  • Presents the recent work on interactive visualization in R.

David W. Gerbing received his PhD from Michigan State University in 1979 in quantitative analysis, and currently is a professor of quantitative analysis in the School of Business at Portland State University. He has published extensively in the social and behavioral sciences with a focus on quantitative methods. His lessR package has been in development since 2009.


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