Parallel chart with the MASS library


This post explains how to build a parallel coordinate chart with R and the MASS library. Note that using ggplot2 is probably a better option.

Parallel coord section ggplot2 option

The parcoord() function of the MASS library.

The MASS library provides the parcoord() function that automatically builds parallel coordinates chart.

The input dataset must be a data frame composed by numeric variables only. Each variable will be used to build one vertical axis of the chart. 

# You need the MASS library
library(MASS)
 
# Vector color
my_colors <- colors()[as.numeric(iris$Species)*11]
 
# Make the graph !
parcoord(iris[,c(1:4)] , col= my_colors  )

Reorder variables

It is important to find the best variable order in your parallel coordinates chart. To change it, just change the order in the input dataset.

Note: the RColorBrewer package is used to generate a nice and reliable color palette. 

# You need the MASS library
library(MASS)
 
# Vector color
library(RColorBrewer)
palette <- brewer.pal(3, "Set1") 
 my_colors <- palette[as.numeric(iris$Species)]

# Make the graph !
parcoord(iris[,c(1,3,4,2)] , col= my_colors  )

Highlight a group

Data visualization aims to highlight a story in the data. If you are interested in a specific group, you can highlight it as follow: 

# You need the MASS library
library(MASS)
 
# Let's use the Iris dataset as an example
data(iris)
 
# Vector color: red if Setosa, grey otherwise.
isSetosa <- ifelse(iris$Species=="setosa","red","grey")

# Make the graph !
parcoord(iris[,c(1,3,4,2)] , col=isSetosa  )

Related chart types
Barplot
Spider / Radar
Wordcloud
Parallel
Lollipop
Circular Barplot



Contact

This document is a work by Yan Holtz. Any feedback is highly encouraged. You can fill an issue on Github, drop me a message on Twitter, or send an email pasting yan.holtz.data with gmail.com.

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