alluvial (version 0.1-2)

alluvial: Alluvial diagram

Description

Drawing alluvial diagrams, also known as parallel set plots.

Usage

alluvial(..., freq, col = "gray", border = 0, layer, hide = FALSE, alpha = 0.5, gap.width = 0.05, xw = 0.1, cw = 0.1, blocks = TRUE, ordering = NULL, axis_labels = NULL, cex = par("cex"), cex.axis = par("cex.axis"))

Arguments

...
vectors or data frames, all for the same number of observations
freq
numeric, vector of frequencies of the same length as the number of observations
col
vector of colors of the stripes
border
vector of border colors for the stripes
layer
numeric, order of drawing of the stripes
hide
logical, should particular stripe be plotted
alpha
numeric, vector of transparency of the stripes
gap.width
numeric, relative width of inter-category gaps
xw
numeric, the distance from the set axis to the control points of the xspline
cw
numeric, width of the category axis
blocks
logical, whether to use blocks to tie the flows together at each category, versus contiguous ribbons (also admits character value "bookends")
ordering
list of numeric vectors allowing to reorder the alluvia on each axis separately, see Examples
axis_labels
character, labels of the axes, defaults to variable names in the data
cex, cex.axis
numeric, scaling of fonts of category labels and axis labels respectively. See par.

Value

Invisibly a list with elements: Invisibly a list with elements:

Examples

Run this code
# Titanic data
tit <- as.data.frame(Titanic)

# 2d
tit2d <- aggregate( Freq ~ Class + Survived, data=tit, sum)
alluvial( tit2d[,1:2], freq=tit2d$Freq, xw=0.0, alpha=0.8,
         gap.width=0.1, col= "steelblue", border="white",
         layer = tit2d$Survived != "Yes" )

alluvial( tit2d[,1:2], freq=tit2d$Freq, 
         hide=tit2d$Freq < 150,
         xw=0.0, alpha=0.8,
         gap.width=0.1, col= "steelblue", border="white",
         layer = tit2d$Survived != "Yes" )

# 3d
tit3d <- aggregate( Freq ~ Class + Sex + Survived, data=tit, sum)

alluvial(tit3d[,1:3], freq=tit3d$Freq, alpha=1, xw=0.2,
         col=ifelse( tit3d$Survived == "No", "red", "gray"),
         layer = tit3d$Sex != "Female",
         border="white")


# 4d
alluvial( tit[,1:4], freq=tit$Freq, border=NA,
         hide = tit$Freq < quantile(tit$Freq, .50),
         col=ifelse( tit$Class == "3rd" & tit$Sex == "Male", "red", "gray") )

# 3d example with custom ordering
# Reorder "Sex" axis according to survival status
ord <- list(NULL, with(tit3d, order(Sex, Survived)), NULL)
alluvial(tit3d[,1:3], freq=tit3d$Freq, alpha=1, xw=0.2,
         col=ifelse( tit3d$Survived == "No", "red", "gray"),
         layer = tit3d$Sex != "Female",
         border="white", ordering=ord)

# Possible blocks options
for (blocks in c(TRUE, FALSE, "bookends")) {
    
    # Elaborate alluvial diagram from main examples file
    alluvial( tit[, 1:4], freq = tit$Freq, border = NA,
              hide = tit$Freq < quantile(tit$Freq, .50),
              col = ifelse( tit$Class == "3rd" & tit$Sex == "Male",
                            "red", "gray" ),
              blocks = blocks )
}


# Data returned
x <- alluvial( tit2d[,1:2], freq=tit2d$Freq, xw=0.0, alpha=0.8,
          gap.width=0.1, col= "steelblue", border="white",
          layer = tit2d$Survived != "Yes" )
points( rep(1, 16), x$endpoints[[1]], col="green")
points( rep(2, 16), x$endpoints[[2]], col="blue")

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