The Many Faces of a Scatterplot

TLDR

Scatterplots are powerful tools for data analysis, and their development is guided by general graphical principles. The study aims to enrich scatterplots with additional graphical features that enhance existing capabilities or introduce entirely new ones. The authors describe a suite of graphical additions—including sunflowers, category codes, point‑cloud sizing, and various smoothing techniques for univariate and bivariate relationships—to extend scatterplot functionality.

Abstract

Abstract The scatterplot is one of our most powerful tools for data analysis. Still, we can add graphical information to scatterplots to make them considerably more powerful. These graphical additions, faces of sorts, can enhance capabilities that scatterplots already have or can add whole new capabilities that faceless scatterplots do not have at all. The additions we discuss here—some new and some old—are (a) sunflowers, (b) category codes, (c) point cloud sizings, (d) smoothings for the dependence of y on x (middle smoothings, spread smoothings, and upper and lower smoothings), and (e) smoothings for the bivariate distribution of x and y (pairs of middle smoothings, sum-difference smoothings, scale-ratio smoothings, and polar smoothings). The development of these additions is based in part on a number of graphical principles that can be applied to the development of statistical graphics in general.