library(vcd)

##################################################
## Hair/Eye Color
##################################################
HairEyeColor
?HairEyeColor
str(HairEyeColor)

## table to df: as.data.frame
df <- as.data.frame(HairEyeColor)
df
## df to table: xtabs
tab <- xtabs(Freq ~ ., data = df)
tab

## structable & mosaic plot: split horiz./vert./horiz./vert./etc.
## don't use for more than four variables
## Convenient layout of table:
structable(~ Hair + Eye, data = df)
## or
structable(~ Hair + Eye + Sex, data = df)

## Mosaic plot without independence test - area is porportional to cell entry
mosaic(~ Hair + Eye, data = df, shade = FALSE)
mosaic(~ Hair + Eye + Sex, data = df, shade = FALSE)
## Mosaic plot with independence test
mosaic(~ Hair + Eye, data = df, shade = TRUE)
## The hyp. "Haircolor and Eyecolor are independent" is clearly rejected (p-value < 2.22*10^-16).
## If you have black hair, it is "surprisingly" likely that you have brown eyes and surprisingly unlikely to have blue eyes.
## If you have blond hair, you are surprisingly unlikely to have brown eyes and surprisingly likely to have blue eyes.

## Make a mosaic plot for each sex:
cotabplot(~ Hair + Eye | Sex, data = df, shade = TRUE)
## The connection blue eyes - blond hair in women is much more striking than in men