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.
parcoord()function of the
MASS library provides the
parcoord() function that automatically builds parallel
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$Species)*11] # Make the graph ! parcoord(iris[,c(1:4)] , col= my_colors )
It is important to find the best variable order in your parallel coordinates chart. To change it, just change the order in the input dataset.
RColorBrewer package is used to
generate a nice and reliable color palette.
# You need the MASS library library(MASS) # Vector color library(RColorBrewer) palette <- brewer.pal(3, "Set1") my_colors <- palette[as.numeric(iris$Species)] # Make the graph ! parcoord(iris[,c(1,3,4,2)] , col= my_colors )
Data visualization aims to highlight a story in the data. If you are interested in a specific group, you can highlight it as follow: