R Visualizations: Derive Meaning from Data

R Visualizations: Deriving 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.
• Offers instruction in the author's visualization system, lessR, which is generally less verbose than ggplot2 and lattice.
• 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.

《R視覺化：從數據中獲得意義》專注於數據分析的兩個主要主題之一：數據可視化，也就是計算機圖形學。在這本書中，我們討論了主要的R視覺化系統，按主題而非系統進行組織。任何進行數據分析的人都將學習如何使用R生成基本的視覺化效果。此外，本書還介紹了作者的lessR系統，該系統在編碼方面比其他系統更簡潔，有時甚至截然不同，並提供相應的統計分析。

主要特點：

- 全面介紹了領先的R視覺化系統ggplot2。
- 提供使用基本R圖形獲得與ggplot2相同質量的視覺化的具體指導。
- 教授作者的視覺化系統lessR，該系統通常比ggplot2和lattice更簡潔。
- 按主題而非系統組織的各種R圖形方法。
- 介紹R中的互動式視覺化的最新工作。

David W. Gerbing於1979年在密歇根州立大學獲得量化分析博士學位，目前是波特蘭州立大學商學院的量化分析教授。他在社會和行為科學領域發表了大量關於量化方法的論文。他的lessR軟件包自2009年以來一直在開發中。

David W. Gerbing has a Quantitative Methods B.A. from Western Washington State College, and M.A. from Michigan State University, and a Ph.D. from Michigan State University. Dr. Gerbing teaches statistics, quantitative methods, and business research techniques. His research interests are in the areas of quantitative analysis, multivariate statistics, and behavioral measurement and assessment. Currently his primary interest is in the increasing the accessibility of the R programming language for data science so that non-programmers can access the free, open source data analysis system without a steep learning curve.

David W. Gerbing擁有西華盛頓州立學院的量化方法學士學位，以及密歇根州立大學的碩士學位和博士學位。Gerbing博士教授統計學、量化方法和商業研究技巧。他的研究興趣涉及量化分析、多變量統計和行為測量和評估等領域。目前，他主要關注的是提高R程式語言在數據科學中的可用性，以便非程式設計師能夠在不需要陡峭的學習曲線的情況下使用這個免費、開源的數據分析系統。