Penguins Go Parallel: A Grammar of Graphics Framework for Generalized Parallel Coordinate Plots
提出广义平行坐标图（GPCP），将传统平行坐标图从仅适用于数值变量扩展到能同时处理分类和数值变量，并在R包ggpcp中实现。
Parallel Coordinate Plots (PCP) are a valuable tool for exploratory data analysis of high-dimensional numerical data. The use of PCPs is limited when working with categorical variables or a mix of categorical and continuous variables. In this article, we propose Generalized Parallel Coordinate Plots (GPCP) to extend the ability of PCPs from just numeric variables to dealing seamlessly with a mix of categorical and numeric variables in a single plot. In this process we find that existing solutions for categorical values only, such as hammock plots or parsets become edge cases in the new framework. By focusing on individual observations rather than a marginal frequency we gain additional flexibility. The resulting approach is implemented in the R package ggpcp. Supplementary materials for this article are available online.