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Plot a graphical matrix where each cell contains a dot whose size reflects the relative magnitude of the corresponding component.
balloonplot(x, ...)
# S3 method for table
balloonplot(x, xlab, ylab, zlab, show.zeros=FALSE,show.margins=TRUE,...)
# S3 method for default
balloonplot(x,y,z,
xlab,
ylab,
zlab=deparse(substitute(z)),
dotsize=2/max(strwidth(19),strheight(19)),
dotchar=19,
dotcolor="skyblue",
text.size=1,
text.color=par("fg"),
main,
label=TRUE,
label.digits=2,
label.size=1,
label.color=par("fg"),
scale.method=c("volume","diameter"),
scale.range=c("absolute","relative"),
colsrt=par("srt"),
rowsrt=par("srt"),
colmar=1,
rowmar=2,
show.zeros=FALSE,
show.margins=TRUE,
cum.margins=TRUE,
sorted=TRUE,
label.lines=TRUE,
fun=function(x)sum(x,na.rm=T),
hide.duplicates=TRUE,
... )Nothing of interest.
A table object, or either a vector or a list of several categorical vectors containing grouping variables for the first (x) margin of the plotted matrix.
Vector or list of vectors for grouping variables for the second (y) dimension of the plotted matrix.
Vector of values for the size of the dots in the plotted matrix.
Text label for the x dimension. This will be displayed on the x axis and in the plot title.
Text label for the y dimension. This will be displayed on the y axis and in the plot title.
Text label for the dot size. This will be included in the plot title.
Maximum dot size. You may need to adjust this value for different plot devices and layouts.
Plotting symbol or character used for dots. See the help page for the points function for symbol codes.
Scalar or vector specifying the color(s) of the dots in the plot.
Character size and color for row and column headers
Plot title text.
Boolean flag indicating whether the actual value of the elements should be shown on the plot.
Number of digits used in formatting value labels.
Character size and color for value labels.
Method of scaling the sizes of the dot, either "volume" or "diameter". See below.
Method for scaling original data to compute
circle diameter. scale.range="absolute" scales the data
relative to 0 (i.e, maps [0,max(z)] --> [0,1]), while
scale.range="relative" scales the data relative to min(z)
(i.e. maps [min(z), max(z)] --> [0,1]).
Angle of rotation for row and column labels.
Space allocated for row and column labels. Each unit is the width/height of one cell in the table.
boolean. If FALSE, entries containing zero will be left
blank in the plotted matrix. If TRUE, zeros will be
displayed.
boolean. If TRUE, row and column sums are
printed in the bottom and right margins, respectively.
boolean. If TRUE, marginal fractions are
graphically presented in grey behind the row/column label area.
boolean. If TRUE, the rows will be
arranged in sorted order by using the levels of the first y factor,
then the second y factor, etc. The same process is used for the
columns, based on the x factors
boolean. If TRUE, borders will be drawn for
row and column level headers.
boolean. If TRUE, column and row headers
will omit duplicates within row/column to reduce clutter. Defaults
to TRUE.
function to be used to combine data elements with the same
levels of the grouping variables x and y. Defaults to sum
Additional arguments passed to balloonplot.default
or plot, as appropriate.
Gregory R. Warnes greg@warnes.net
This function plots a visual matrix. In each x,y cell a
dot is plotted which reflects the relative size of the corresponding
value of z. When scale.method="volume" the volume of
the dot is proportional to the relative size of z. When
scale.method="diameter", the diameter of the dot is proportional to
the the relative size of z. The "volume" method is default
because the "diameter" method visually exaggerates differences.
Function inspired by question posed on R-help by Ramon Alonso-Allende allende@cnb.uam.es.
# \testonly{
set.seed(12425421)
# }
# Create an Example Data Frame Containing Car x Color data
carnames <- c("bmw","renault","mercedes","seat")
carcolors <- c("red","white","silver","green")
datavals <- round(rnorm(16, mean=100, sd=60),1)
data <- data.frame(Car=rep(carnames,4),
Color=rep(carcolors, c(4,4,4,4) ),
Value=datavals )
# show the data
data
# generate balloon plot with default scaling
balloonplot( data$Car, data$Color, data$Value)
# show margin label rotation & space expansion, using some long labels
levels(data$Car) <- c("BMW: High End, German","Renault: Medium End, French",
"Mercedes: High End, German", "Seat: Imaginary, Unknown Producer")
# generate balloon plot with default scaling
balloonplot( data$Car, data$Color, data$Value, colmar=3, colsrt=90)
# Create an example using table
xnames <- sample( letters[1:3], 50, replace=2)
ynames <- sample( 1:5, 50, replace=2)
tab <- table(xnames, ynames)
balloonplot(tab)
# Example of multiple classification variabls using the Titanic data
library(datasets)
data(Titanic)
dframe <- as.data.frame(Titanic) # convert to 1 entry per row format
attach(dframe)
balloonplot(x=Class, y=list(Survived, Age, Sex), z=Freq, sort=TRUE)
# colorize: surviors lightblue, non-survivors: grey
Colors <- Titanic
Colors[,,,"Yes"] <- "skyblue"
Colors[,,,"No"] <- "grey"
colors <- as.character(as.data.frame(Colors)$Freq)
balloonplot(x=list(Age,Sex),
y=list(Class=Class,
Survived=reorder.factor(Survived,new.order=c(2,1))
),
z=Freq,
zlab="Number of Passengers",
sort=TRUE,
dotcol = colors,
show.zeros=TRUE,
show.margins=TRUE)
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