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 class 'table'
balloonplot(x, xlab, ylab, zlab, show.zeros=FALSE,show.margins=TRUE,...)
# Default S3 method
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,
                                ... )

Arguments

x: 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.
y: Vector or list of vectors for grouping variables for the second (y) dimension of the plotted matrix.
z: Vector of values for the size of the dots in the plotted matrix.
xlab: Text label for the x dimension. This will be displayed on the x axis and in the plot title.
ylab: Text label for the y dimension. This will be displayed on the y axis and in the plot title.
zlab: Text label for the dot size. This will be included in the plot title.
dotsize: Maximum dot size. You may need to adjust this value for different plot devices and layouts.
dotchar: Plotting symbol or character used for dots. See the help page for the points function for symbol codes.
dotcolor: Scalar or vector specifying the color(s) of the dots in the plot.
text.size, text.color: Character size and color for row and column headers
main: Plot title text.
label: Boolean flag indicating whether the actual value of the elements should be shown on the plot.
label.digits: Number of digits used in formatting value labels.
label.size, label.color: Character size and color for value labels.
scale.method: Method of scaling the sizes of the dot, either "volume" or "diameter". See below.
scale.range: 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]).
rowsrt, colsrt: Angle of rotation for row and column labels.
rowmar, colmar: Space allocated for row and column labels. Each unit is the width/height of one cell in the table.
show.zeros: boolean. If FALSE, entries containing zero will be left blank in the plotted matrix. If TRUE, zeros will be displayed.
show.margins: boolean. If TRUE, row and column sums are printed in the bottom and right margins, respectively.
cum.margins: boolean. If TRUE, marginal fractions are graphically presented in grey behind the row/column label area.
sorted: 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
label.lines: boolean. If TRUE, borders will be drawn for row and column level headers.
hide.duplicates: boolean. If TRUE, column and row headers will omit duplicates within row/column to reduce clutter. Defaults to TRUE.
fun: 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.

Details

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.

Value

Nothing of interest.

Note

z is expected to be non-negative. The function will still operate correctly if there are negative values of z, but the corresponding dots will have 0 size and a warning will be generated.

References

Function inspired by question posed on R-help by Ramon Alonso-Allende allende@cnb.uam.es.

Author

Gregory R. Warnes greg@warnes.net

Examples


# 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
#>         Car  Color Value
#> 1       bmw    red  93.6
#> 2   renault    red 190.7
#> 3  mercedes    red  94.3
#> 4      seat    red 221.1
#> 5       bmw  white  96.2
#> 6   renault  white 178.3
#> 7  mercedes  white 237.2
#> 8      seat  white  16.7
#> 9       bmw silver  83.3
#> 10  renault silver  92.0
#> 11 mercedes silver 138.2
#> 12     seat silver  82.9
#> 13      bmw  green -59.4
#> 14  renault  green -46.4
#> 15 mercedes  green 179.2
#> 16     seat  green  81.6

# 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)