Modern Data Visualization with R

Modern Data Visualization with R describes the many ways that raw and summary data can be turned into visualizations that convey meaningful insights. It starts with basic graphs such as bar charts, scatter plots, and line charts, but progresses to less well-known visualizations such as tree maps, alluvial plots, radar charts, mosaic plots, effects plots, correlation plots, biplots, and the mapping of geographic data. Both static and interactive graphics are described and the use of color, shape, shading, grouping, annotation, and animations are covered in detail. The book moves from a default look and feel for graphs, to graphs with customized colors, fonts, legends, annotations, and organizational themes.

Features:

- Contains a wide breadth of graph types including newer and less well-known approaches
- Connects each graph type to the characteristics of the data and the goals of the analysis
- Moves the reader from simple graphs, describing one variable, to building visualizations that describe complex relationships among many variables
- Newer approaches to creating interactive web graphics via JavaScript libraries
- Details how to customize each graph type to meet users' needs and those of their audiences
- Gives methods for creating visualizations that are publication ready for print (in color or black and white) and the web
- Suggests best practices
- Offers examples from a wide variety of fields

It is written for those new to data analysis as well as the seasoned data scientist. It can be used for both teaching and research. It will particularly appeal to anyone who needs to describe data visually and wants to find and emulate the most appropriate method quickly. The reader should have some basic coding experience, but expertise in R is not required. Some of the later chapters (e.g., visualizing statistical models) assume exposure to statistical inference at the level of analysis of variance and regression.

《現代資料視覺化與 R》描述了將原始和摘要資料轉化為傳達有意義洞察的視覺化的多種方法。它從基本的圖表開始，如長條圖、散點圖和折線圖，然後進展到較不常見的視覺化，如樹狀圖、全流圖、雷達圖、馬賽克圖、效果圖、相關圖、雙標圖和地理數據的映射。書中詳細介紹了靜態和互動圖形，並涵蓋了顏色、形狀、陰影、分組、註釋和動畫的使用。本書從圖形的默認外觀開始，進而介紹了具有自定義顏色、字體、圖例、註釋和組織主題的圖形。

特點：
- 包含多種圖形類型，包括較新且較不常見的方法
- 將每種圖形類型與數據的特性和分析目標相關聯
- 從描述單變量的簡單圖形開始，進而構建描述多個變量之間複雜關係的視覺化
- 介紹使用 JavaScript 函式庫創建互動網頁圖形的新方法
- 詳細介紹如何根據用戶和觀眾的需求自定義每種圖形類型
- 提供創建適合印刷（彩色或黑白）和網頁的出版就緒視覺化的方法
- 提供最佳實踐建議
- 提供來自各個領域的示例

本書適合初次接觸資料分析和經驗豐富的資料科學家閱讀，可用於教學和研究。它尤其適合需要以視覺方式描述資料並希望快速找到並模仿最適方法的人。讀者應具備一些基本的編程經驗，但不需要精通 R。部分後面的章節（例如，視覺化統計模型）假設讀者具有方差分析和回歸分析等統計推論的知識。

Robert Kabacoff is a data scientist with more than 30 years of experience in multivariate statistical methods, data visualization, predictive analytics, and psychometrics. A widely recognized expert in statistical programming, he is the author of R in Action: Data Analysis and Graphics with R (3rd ed.), and the popular Quick-R (www.statmethods.net) website. Dr. Kabacoff is also the co-author of Evaluating Research Articles from Start to Finish (3rd ed.), a textbook that uses a case-study approach to help students learn to read and evaluate empirical research.

Dr. Kabacoff earned his BA in psychology from the University of Connecticut and his PhD in clinical psychology from the University of Missouri-St. Louis. Following a postdoctoral fellowship in family research at Brown University, he joined the faculty at the Center for Psychological Studies at Nova Southeastern University, achieving the position of full professor in 1997. For 19 years, Dr. Kabacoff held the position of Vice President of Research for a global organizational development firm, providing research and consultation to academic, government, corporate, and humanitarian institutions in North America, Western Europe, Africa, and Asia. He is currently a professor of the practice in quantitative analysis at the Hazel Quantitative Analysis Center at Wesleyan University, teaching courses in exploratory data analysis, machine learning, and statistical software development.

Robert Kabacoff是一位資料科學家，擁有超過30年的多變量統計方法、資料視覺化、預測分析和心理測量學的經驗。作為統計程式設計的廣泛認可專家，他是《R in Action: Data Analysis and Graphics with R (第3版)》和知名的《Quick-R》(www.statmethods.net)網站的作者。Kabacoff博士還是《Evaluating Research Articles from Start to Finish (第3版)》的合著者，這是一本使用案例研究方法幫助學生學習閱讀和評估實證研究的教科書。

Kabacoff博士在康涅狄格大學獲得心理學學士學位，並在密蘇里州立大學聖路易斯分校獲得臨床心理學博士學位。在布朗大學進行家庭研究的博士後研究員期間，他加入了諾瓦東南大學心理研究中心的教職人員，並於1997年晉升為正教授。在接下來的19年裡，Kabacoff博士擔任全球組織發展公司的研究副總裁，為北美、西歐、非洲和亞洲的學術、政府、企業和人道主義機構提供研究和諮詢服務。他目前是韋斯利安大略大學Hazel Quantitative Analysis Center的量化分析實踐教授，教授探索性數據分析、機器學習和統計軟件開發課程。