Hands-on Exercise 5d: Visual Multivariate Analysis with Parallel Coordinates Plot

Published

February 7, 2024

Modified

February 8, 2024

1 Getting Started

In this exercise, we will use the following our R packages.

  • ggparcoord() of GGally package to plot statistic parallel coordinates plot,

  • parcoords package to plot interactive parallel coordinates plots, and

  • parallelPlot package to plot interactive parallel coordinates plots.

The code chunk below uses p_load() of pacman package to check if these packages are installed in the computer and load them onto your working R environment.

pacman::p_load(GGally, parallelPlot, tidyverse)

The code chunk below imports WHData-2018.csv into R environment by using read_csv() function of readr package.

wh <- read_csv("data/WHData-2018.csv")

2 Plotting Static Parallel Coordinates Plot

2.1 A simple parallel coordinates

Code chunk below shows a typical syntax used to plot a basic static parallel coordinates plot by using ggparcoord().

ggparcoord(data = wh, 
           columns = c(7:12))

Note

Notice that only two argument namely data and columns is used. Data argument is used to map the data object (i.e. wh) and columns is used to select the columns for preparing the parallel coordinates plot.

2.2 A parallel coordinates with boxplot

The basic parallel coordinates failed to reveal any meaning understanding of the World Happiness measures. In this section, ggparcoord() will be used to makeover the plot.

ggparcoord(data = wh, 
           columns = c(7:12), 
           groupColumn = 2,
           scale = "uniminmax",
           alphaLines = 0.2,
           boxplot = TRUE, 
           title = "Parallel Coordinates Plot of World Happines Variables")

Things to learn from the code chunk above

  • groupColumn argument is used to group the observations (i.e. parallel lines) by using a single variable (i.e. Region) and colour the parallel coordinates lines by region name.

  • scale argument is used to scale the variables in the parallel coordinate plot by using uniminmax method. The method univariately scale each variable so the minimum of the variable is zero and the maximum is one.

  • alphaLines argument is used to reduce the intensity of the line color to 0.2. The permissible value range is between 0 to 1.

  • boxplot argument is used to turn on the boxplot by using logical TRUE. The default is FALSE.

  • title argument is used to provide the parallel coordinates plot a title.

2.3 Parallel coordinates with facet

In the code chunk below, facet_wrap() of ggplot2 is used to plot 10 small multiple parallel coordinates plots. Each plot represent one geographical region such as East Asia.

ggparcoord(data = wh, 
           columns = c(7:12), 
           groupColumn = 2,
           scale = "uniminmax",
           alphaLines = 0.2,
           boxplot = TRUE, 
           title = "Multiple Parallel Coordinates Plots of World Happines Variables by Region") +
  facet_wrap(~ Region)

2.4 Rotating x-axis text label

We can rotate axis text labels using theme() function in ggplot2 as shown in the code chunk below.

ggparcoord(data = wh, 
           columns = c(7:12), 
           groupColumn = 2,
           scale = "uniminmax",
           alphaLines = 0.2,
           boxplot = TRUE, 
           title = "Multiple Parallel Coordinates Plots of World Happines Variables by Region") +
  facet_wrap(~ Region) + 
  theme(axis.text.x = element_text(angle = 30))

Things to learn from the code chunk above
  • To rotate x-axis text labels, we use axis.text.x as argument to theme() function. And we specify element_text(angle = 30) to rotate the x-axis text by an angle 30 degree.

2.5 Adjusting the rotated x-axis text label

Rotating x-axis text labels to 30 degrees makes the label overlap with the plot and we can avoid this by adjusting the text location using hjust argument to theme’s text element with element_text(). We use axis.text.x as we want to change the look of x-axis text.

ggparcoord(data = wh, 
           columns = c(7:12), 
           groupColumn = 2,
           scale = "uniminmax",
           alphaLines = 0.2,
           boxplot = TRUE, 
           title = "Multiple Parallel Coordinates Plots of World Happines Variables by Region") +
  facet_wrap(~ Region) + 
  theme(axis.text.x = element_text(angle = 30, hjust=1))

3 Plotting Interactive Parallel Coordinates Plot: parallelPlot methods

In this section, parallelPlot will be used to build interactive parallel coordinates plot.

3.1 The basic plot

The code chunk below plot an interactive parallel coordinates plot by using parallelPlot().

wh <- wh %>%
  select("Happiness score", c(7:12))
parallelPlot(wh,
             width = 320,
             height = 250)

3.2 Rotate axis label

In the code chunk below, rotateTitle argument is used to avoid overlapping axis labels.

parallelPlot(wh,
             rotateTitle = TRUE)

3.3 Changing the color scheme

We can change the default blue color scheme by using continousCS argument as shown in the code chunk below.

parallelPlot(wh,
             continuousCS = "YlOrRd",
             rotateTitle = TRUE)

3.4 Parallel coordinates plot with histogram

In the code chunk below, histoVisibility argument is used to plot histogram along the axis of each variables.

histoVisibility <- rep(TRUE, ncol(wh))
parallelPlot(wh,
             rotateTitle = TRUE,
             histoVisibility = histoVisibility)