This silly package, ggChernoff, introduces a geom_chernoff geom for ggplot2. This works a bit like geom_point, but draws little smiley faces (emoticons) instead of dots.
The Chernoff geom has some unique aesthetics, including smile, which makes your faces smile or frown according to the relative magnitude of your continuous variable. By default, the mean value will generate a straight face 😑 while higher values will make smiles 😊 and lower values will draw frowns 😢. You can customise this using scale_smile. If smile is unmapped to a variable, all faces will be happy by default.
Eyebrows are hidden by default, but you can activate them by mapping something to the brow aesthetic. High values make your faces angry :angry: and low values the opposite :anguished:.
Install the package using
devtools::install_github('Selbosh/ggChernoff')
and then load it using
Firstly, let’s create a scatter plot of smiley faces out of Fisher’s iris data set, each one coloured according to species.
library(ggplot2) ggplot(iris) + aes(Petal.Width, Petal.Length, fill = Species) + geom_chernoff()
Here is an example using Immer’s barley data. We are happy about larger yields!
ggplot(lattice::barley) +
aes(year, variety, smile = yield, brow = yield) +
geom_chernoff(fill = 'goldenrod1') +
scale_x_discrete(limits = c('1931', '1932')) +
facet_wrap(~ site)
Basic legends are now supported. We can customise breaks and titles in the usual ggplot2 way, via scale_smile_continuous.
g <- ggplot(data.frame(x = rnorm(20), y = rexp(20), z = runif(20))) + aes(x, y, smile = z) + geom_chernoff(fill = 'steelblue1') g
g + scale_smile_continuous('Smilez', breaks = 0:10/10, midpoint = .5)
You can also use this command to adjust the range of possible happiness/sadness in your plot. In the following example, everybody is somewhere between sad and straight-faced.
g + scale_smile_continuous(range = c(-1, 0))
New feature as of 0.3.0: eye separation.
ggplot(iris) + aes(Petal.Width, Petal.Length, fill = Species, eyes = Sepal.Length) + geom_chernoff() + scale_eyes_continuous(range = c(0, 2))
cannon <- data.frame(x = 0, y = 0, colour = 'white', size = 20)
bunkers <- data.frame(x = seq(-4, 4, l = 4), y = 2, colour = 'green', size = 1)
ufos <- data.frame(x = rep(seq(-6, 6, length.out = 12), 5),
y = rep(6:10, each = 12), size = 10,
colour = c('cyan', 'yellow', 'magenta')[
c(rep(1:3,4), rep(c(2,3,1),4), rep(c(3,1,2),4), rep(1:3,4), rep(c(2,3,1),4))
],
brow = rnorm(60))
ggplot(ufos) +
aes(x, y, fill = colour, size = size) +
geom_chernoff(smile = -1, aes(brow = brow), eyes = .5) +
geom_chernoff(data = cannon) +
geom_tile(data = bunkers, width = 1) +
geom_tile(data = data.frame(x = 0, y = 3, colour = 'white', size = 2), width = .1) +
scale_fill_identity() +
scale_size_identity() +
theme_void() +
theme(plot.background = element_rect(fill = 'black'),
legend.position = 'none')
#> Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
#> ℹ Please use `linewidth` instead.
Hermann Chernoff (1973). The use of faces to represent points in k-dimensional space graphically. Journal of the American Statistical Association, 68(342), 361–368.
Leland Wilkinson (2006). The Grammar of Graphics (2nd edition). Springer.
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