Enhanced parallel coordinate plots.

pcp draws a parallel coordinate plot.It is a modified version of parcoord {MASS}. Variables may be reordered and panels colored in the display.

catpcp draws a parallel coordinate plot variant for categorical data.

Usage

pcp(data, order = NULL, panel.colors = NULL, col = 1, lty = 1, 
horizontal = TRUE, mar = NULL, scale = TRUE, axis.width = 0,
axis.grid.col="grey70",connect=TRUE, ...)

catpcp(data, order = NULL, pcpbars, barvars = 1:ncol(data), 
pcpbars.border = "black", pcpbars.col = NULL, pcpbars.labels = FALSE, 
pcpbars.axis.at = NULL, pcpbars.axis.labels = NULL, 
axis.width = 0.2,connect=TRUE, ...)

Arguments

data: A data frame or matrix.
order: an index vector specifying variable order. If NULL, all variables are used.
panel.colors: either a vector or a matrix of panel colors. If a vector is supplied, the ith color is used for the ith panel. If a matrix, dimensions should match those of the variables. Diagonal entries are ignored.
col: a vector of colours, recycled as necessary for each observation.
lty: a vector of line types, recycled as necessary for each observation.
horizontal: If TRUE, orientation is horizontal.
mar: margin parameters, passed to par.
scale: If TRUE, the variables are scaled to the unit interval.
axis.width: Width of each of the parallel axes.
axis.grid.col: Color of variable axes. Use NULL for no axes.
connect: If FALSE, line segments are not connected. Points are drawn if axis.width=0.
pcpbars: A list, with one component per barvar. Component i is a matrix with the bottom and top of the bars for that variable.
barvars: Categorical variables where overlayed bars show the level frequency.
pcpbars.border: Border colour of the bars.
pcpbars.col: Colour of the bars.
pcpbars.labels: Labels for the bars.
pcpbars.axis.at: Axis label positions for the bars.
pcpbars.axis.labels: Axis label text for the bars.
...: other parameters, passed to pcp by catpcp

Examples

require(PairViz)     
y <- as.data.frame(as.table(HairEyeColor))

colvar <- 3 # any of 1:3 will do
y <- y[order(y[,colvar]),] # ensures that cases are ordered by colour within each factor level
ylong <- apply(y[,-4],2, function(x) rep(x,times=y[,4]))

cols <- desaturate_color(rainbow(4,alpha=0.3),.5)
cols <- cols[as.numeric(as.factor(ylong[,colvar]))]




ds <- factor_spreadout(ylong)




dev.new(width=5,height=2.5)
par(mar=c(2,1,2,1))
par( cex.axis=.8,cex=.8)



catpcp(ds$data,col=cols,lwd=2,pcpbars=ds$bars,pcpbars.labels=TRUE,main="Hair Eye data")