The geom you always wished for adding cats to ggplot2. This package is part of the memeverse. The source code of this package is based on geom_image from ggimage.
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A collection of funny packages which can be interesting to create plots to show on a first lesson to new R students in order to motivate them learning the language. The other package of the (small) memeverse is ggbernie. Statistics and programming can be fun!
# install.packages("remotes")
remotes::install_github("R-CoderDotCom/ggcats@main")
There are 15 cats available:
"nyancat" (default), "bongo", "colonel", "grumpy", "hipster", "lil_bub", "maru",
"mouth", "pop", "pop_close", "pusheen", "pusheen_pc", "toast", "venus" and "shironeko"
grid <- expand.grid(1:5, 3:1)
df <- data.frame(x = grid[, 1],
y = grid[, 2],
image = c("nyancat", "bongo", "colonel", "grumpy", "hipster",
"lil_bub", "maru", "mouth", "pop", "pop_close",
"pusheen", "pusheen_pc", "toast", "venus", "shironeko"))
library(ggplot2)
ggplot(df) +
geom_cat(aes(x, y, cat = image), size = 5) +
xlim(c(0.25, 5.5)) +
ylim(c(0.25, 3.5))
ggplot(mtcars) +
geom_cat(aes(mpg, wt), cat = "nyancat", size = 5)
ggplot(mtcars) +
geom_cat(aes(mpg, wt, size = cyl), cat = "toast")
I took the most part of the following code from Jonathan Hersh.
library(Ecdat)
data(incomeInequality)
library(tidyverse)
library(ggcats)
library(gganimate)
dat <-
incomeInequality %>%
select(Year, P99, median) %>%
rename(income_median = median,
income_99percent = P99) %>%
pivot_longer(cols = starts_with("income"),
names_to = "income",
names_prefix = "income_")
dat$cat <- rep(NA, 132)
dat$cat[which(dat$income == "median")] <- "nyancat"
dat$cat[which(dat$income == "99percent")] <- rep(c("pop_close", "pop"), 33)
ggplot(dat, aes(x = Year, y = value, group = income, color = income)) +
geom_line(size = 2) +
ggtitle("ggcats, a core package of the memeverse") +
geom_cat(aes(cat = cat), size = 5) +
xlab("Cats") +
ylab("Cats") +
theme(legend.position = "none",
plot.title = element_text(size = 20),
axis.text = element_blank(),
axis.ticks = element_blank()) +
transition_reveal(Year)