ggparallel (version 0.2.0)

ggparallel: Variations of parallel coordinate plots


ggparallel implements and combines different types of parallel coordinate plots for categorical data: hammock plots, parallel sets plots, common angle plots, and common angle plots with a hammock-like adjustment for line widths.


ggparallel(vars = list(), data, weight = NULL, method = "angle", alpha = 0.5, width = 0.25, order = 1, ratio = NULL, asp = NULL, label = TRUE, label.size = 4, text.angle = 90, text.offset = NULL, same.level = FALSE, ...)


list of variable names to be included in the plotting. Order of the variables is preserved in the display
data frame
weighting variable - use character string
plotting method to use - one of angle, adj.angle, parset, or hammock, for a hammock plot the aspect ratio needs to be fixed.
level of alpha blending for the fill color in ribbons, value has to be between 0 and 1, defaults to 0.5.
width of variables
flag variable with three levels -1, 0, 1 for levels in decreasing order, levels in increasing order and levels unchanged. This variable can be either a scalar or a vector
used for methods with angle adjustments (method = 'hammock', 'adj.angle'): specifies the height (width for horizontal displays) of the widest line as ratio of the overall display height (width for horizontal displays).
aspect ratio of the plot - it will be set to a default of 1 in the case of hammock plots.
binary variable (vector), whether labels should be shown.
numeric value to determine the size in which labels are shown, defaults to 4
numeric value in degrees, by which text for labelling is rotated. Ignored if label = FALSE
(vector) of values for offset the labels
are all variables using the same levels? If yes, simplify the labelling
passed on directly to all of the ggplot2 commands


returns a ggplot2 object that can be plotted directly or used as base layer for additional modifications.


Parallel sets have been suggested by kosara:2006 as a visualization technique to incorporate categorical variables into a parallel coordinate plot introduced by wegman:1990 and inselberg:1985. The parallel sets implemented here are reduced to representations of neighboring two-dimensional relationships only rather than the hierarchical version originally suggested.

Both versions, however, show perceptual problems with interpreting line widths, leading to potentially wrong conclusions about the data. The hammock display, introduced by schonlau:2003, and the common angle plots are two approaches at fixing this problem: in Hammock plots the linewidth is adjusted by a factor countering the strength of the illusion, in the common angle plot all lines are adjusted to show the same angle - making line widths again comparable across ribbons.

Additionally, we can also adjust ribbons in the common angle display for the angle, to make them appear having the same width (or height) across the display. We refer to this method as adj.angle.


Run this code

ggparallel(list("gear", "cyl"), data=mtcars)
ggparallel(list("gear", "cyl"), data=mtcars, method="hammock", ratio=0.25)

cols <- c(brewer.pal(4, "Reds")[-1], brewer.pal(4, "Blues")[-1])
ggparallel(list("gear", "cyl"), ratio=0.2, data=mtcars,
           method="hammock", text.angle=0) +
  scale_fill_manual(values=cols) + scale_colour_manual(values=cols) +

## combination of common angle plot and hammock adjustment:
ggparallel(list("gear", "cyl"), data=mtcars, method="adj.angle",

## compare with method='parset'
ggparallel(list("gear", "cyl"), data=mtcars, method='parset')

## flip plot and rotate text
ggparallel(list("gear", "cyl"), data=mtcars, text.angle=0) +

## change colour scheme
ggparallel(list("gear", "cyl"), data=mtcars, text.angle=0) +
  coord_flip() +
  scale_fill_brewer(palette="Set1") +

## example with more than two variables:
titanic <-
ggparallel(names(titanic)[c(1,4,2,1)], order=0, titanic, weight="Freq") +
  scale_fill_brewer(palette="Paired", guide="none") +
  scale_colour_brewer(palette="Paired", guide="none")

## Not run: 
# cols <- c(brewer.pal(5,"Blues")[-1], brewer.pal(3, "Oranges")[-1],
#           brewer.pal(3, "Greens")[-1])
# ggparallel(names(titanic)[c(1,4,2,1)], order=0, titanic, weight="Freq") +
#   scale_fill_manual(values=cols, guide="none") +
#   scale_colour_manual(values=cols, guide="none") + theme_bw()
# ## hammock plot with same width lines
# ggparallel(names(titanic)[c(1,4,2,3)], titanic, weight=1, asp=0.5,
#            method="hammock", ratio=0.2, order=c(0,0)) +
# theme( legend.position="none") +
# scale_fill_brewer(palette="Paired") +
# scale_colour_brewer(palette="Paired")
# ## hammock plot with line widths adjusted by frequency
# ggparallel(names(titanic)[c(1,4,2,3)], titanic, weight="Freq",
#            asp=0.5, method="hammock", order=c(0,0), text.angle=0,
#            width=0.45) +
#   theme( legend.position="none")
# ## biological examples: genes and pathways
# data(genes)
# cols <- c(rep("grey80", 24), brewer.pal("YlOrRd", n = 9))
# genes$chrom <- factor(genes$chrom, levels=c(paste("chr", 1:22, sep=""), "chrX", "chrY"))
# ggparallel(list("path", "chrom"), text.offset=c(0.03, 0,-0.03),
#            data = genes,  width=0.1, order=c(1,0), text.angle=0,
#            color="white",
#    factorlevels =  c(sapply(unique(genes$chrom), as.character),
#      unique(genes$path))) +
#    scale_fill_manual(values = cols, guide="none") +
#    scale_colour_manual(values = cols, guide="none") +
#    coord_flip()
# ## End(Not run)

titanic <-

titanic$SexSurvived <- with(titanic, interaction(Sex, Survived))
titanic$SexClassSurvived <- with(titanic, interaction(Sex,Class, Survived))

ggparallel(vars=list("Survived", "SexSurvived", "SexClassSurvived"), weight="Freq", data=titanic) +
  theme(legend.position="none") +
  scale_fill_manual(values = rep(c("Orange", "Steelblue"), 14)) +
  scale_colour_manual(values = rep(c("Orange", "Steelblue"), 14))

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