The Parallel Coordinates Plot Revisited: Visual Extensions from Hive Plots, Heterogeneous Correlations, and an Exploration of Covid-19 Data in the United States

TL;DR

This paper enhances the Parallel Coordinates Plot by integrating Hive Plot techniques and polar coordinates, enabling better exploration of multidimensional and 3D data, demonstrated through various datasets including Covid-19 data.

Contribution

It introduces a novel extension of PCP using Hive Plot techniques and polar coordinates for improved multidimensional data visualization.

Findings

Enhanced visualization of 3D data in PCPs

Effective exploration of Covid-19 county data

Demonstrated utility on multiple datasets

Abstract

This paper extends an existing visualization, the Parallel Coordinates Plot (PCP), specifically its polar coordinate representation, the $\textit{Polar Parallel Coordinates Plot (P2CP)}$. With the additional incorporation of techniques borrowed from Hive Plot network visualizations, we demonstrate improved capabilities to explore multidimensional data in flatland, with a particular emphasis on the unique ability to represent 3-dimensional data. To demonstrate these techniques on P2CPs, we consider toy data, the Iris dataset, and socioeconomic data for counties in the United States. We conclude with an exploration of Covid-19 data from counties in the contiguous United States.