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Activity Number: 405 - Student Paper Award and Chambers Statistical Software Award
Type: Topic Contributed
Date/Time: Wednesday, August 5, 2020 : 1:00 PM to 2:50 PM
Sponsor: Section on Statistical Computing
Abstract #309767
Title: A Grammar of Graphics Framework for Generalized Parallel Coordinate Plots
Author(s): Yawei Ge* and Heike Hofmann
Companies: Iowa State Univ and Iowa State University
Keywords: highdimensional visualization; data exploration; categorical variables
Abstract:

Parallel coordinate plots (PCP) are a useful tool in 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 paper, 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 observation rather a marginal frequency we gain additional flexibility. The resulting approach is implemented in the R package ggpcp.


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