Parallel chart with the MASS library in R (original) (raw)

Last Updated : 23 Jul, 2025

To analyze and visualize high-dimensional data, one can use Parallel Coordinates. A background is drawn consisting of n parallel lines, often vertical and evenly spaced, to display a set of points in an n-dimensional space. A point in n-dimensional space is represented by a polyline with vertices on parallel axes; the ith coordinate of the point corresponds to the position of the vertex on the ith axis.

Parallel chart with the MASS library in R Programming Language

This representation is similar to time series visualization, except that it is used with data that does not have a natural order because the axes do not correlate to points in time. As a result, several axis layouts may be of interest.

Parallel Coordinates with MASS Library

The parcoord() function in the MASS package creates a parallel coordinates chart automatically. A data frame with solely numeric variables can be used as the input dataset. Each variable will be utilized to construct one of the chart's vertical axes.

R `

Libraries

library(MASS)

default data in R

data <- iris

head(data)

plotting the graphs

parcoord(iris[, c(1:4)] , # choosing first 4 parameters

     # selecting the color palette based on the plot
     col = colors()[as.numeric(iris$Species)*8] 
     )

Output:

Sepal.Length Sepal.Width Petal.Length Petal.Width Species 1 5.1 3.5 1.4 0.2 setosa 2 4.9 3.0 1.4 0.2 setosa 3 4.7 3.2 1.3 0.2 setosa 4 4.6 3.1 1.5 0.2 setosa 5 5.0 3.6 1.4 0.2 setosa 6 5.4 3.9 1.7 0.4 setosa

Customizing the Color Palette

Basically, there are not any built-in methods or attributes in this package for color customization. We will use colorRampPalette() methods color range between two colors specified points

R `

Libraries

library(MASS)

choosing the graph color

library(RColorBrewer)