main.R

# INSTALL GGCATS PACKAGE AND ECDAT

install.packages("remotes")
remotes::install_github("R-CoderDotCom/ggcats@main")
install.packages("Ecdat")

# LOAD LIBRARIES

library(ggplot2)
library(ggcats)
library(tidyverse)
library(gganimate)

# VISUALIZE AVAILABLE CATS

theGrid <- expand.grid(1:5, 3:1)
dataFrame <- data.frame(x = theGrid[, 1],
                 y = theGrid[, 2],
                 image = c("shironeko", "venus", "hipster", "lil_bub", "maru", 
                           "colonel", "grumpy", "mouth", "pop", "pop_close", 
                           "pusheen", "pusheen_pc", "toast", "bongo", "nyancat"))

ggplot(dataFrame) +
  geom_cat(aes(x, y, cat = image), size = 4) +
  xlim(c(0.30, 5.5)) + 
  ylim(c(0.30, 3.5))

# TESTING PUSHEEN CAT AND MARU CAT

ggplot(mtcars) +
  geom_cat(aes(mpg, wt), cat = "pusheen", size = 4)

ggplot(mtcars) +
  geom_cat(aes(mpg, wt, size = cyl), cat = "maru")

# EXAMPLE GGCAT WITH GGANIMATE 

library(Ecdat)

data(incomeInequality)

newData <-
  incomeInequality %>%
  select(Year, P99, median) %>%
  rename(income_median = median,
         income_99percent = P99) %>%
  pivot_longer(cols = starts_with("income"),
               names_to = "income",
               names_prefix = "income_")

newData$cat <- rep(NA, 132)

newData$cat[which(newData$income == "median")] <- rep(c("pop_close", "pop"), 33)
newData$cat[which(newData$income == "99percent")] <- "bongo" 

ggplot(newData, aes(x = Year, y = value, group = income, color = income)) +
  geom_line(size = 2.5) +
  labs(title="Testing ggcats with gganimate", 
       subtitle = "Pop cat and Bongo cat") +
  geom_cat(aes(cat = cat), size = 6) +
  transition_reveal(Year)