Area-Proportional Visualization for Circular Data. Issue 2 (2nd April 2020)

• Record Type: Journal Article
• Authors: Xu, Danli; Wang, Yong
• Is Part Of: Journal of computational and graphical statistics. Volume 29:Issue 2(2020)
• Page Start: 351
• Page End: 357
• Publication Date: 2020-04-02
• Subjects: Circular data -- Circular plot -- Density visualization -- Dot plot -- Histogram -- Rose diagram; Mathematical statistics -- Data processing -- Periodicals; Mathematical statistics -- Graphic methods -- Periodicals; 519.50285
• DOI: 10.1080/10618600.2019.1654881
• Languages: English
• ISSNs: 1061-8600

Abstract

Abstract: Data visualization is important for statistical analysis, as it helps convey information efficiently and shed lights on the hidden patterns behind data in a visual context. It is particularly helpful to display circular data in a two-dimensional space to accommodate its nonlinear support space and reveal the underlying circular structure which is otherwise not obvious in one-dimension. In this article, we first formally categorize circular plots into two types, either height- or area-proportional, and then describe a new general methodology that can be used to produce circular plots, particularly in the area-proportional manner, which in our opinion is the more appropriate choice. Formulas are given that are fairly simple yet effective to produce various circular plots, such as smooth density curves, histograms, rose diagrams, dot plots, and plots for multiclass data. Supplemental materials for this article are available online.