The Data

The data this week comes from the American Kennel Club courtesy of KKakey - thanks!

breed_rank <- read_csv("breed_rank.csv")
breed_traits <- read_csv("breed_traits.csv")
trait_descr <- read_csv("trait_description.csv")

Some plots

My first challenge today is to be able to put the Breed variable on the right side of the line plot which describes year (x-axis) and rank (y-axis). First, the data will need to pivot_longer() to create a tidy format that will be easier to use.

rank <- breed_rank %>%
  pivot_longer(`2013 Rank`:`2020 Rank`, names_to = "year", values_to = "rank") %>%
  mutate(year = parse_number(year))
rank %>%
  filter(rank <= 10) %>%
  mutate(breed = ifelse(year == 2020, Breed, NA)) %>%
  ggplot(aes(x = year, y = rank, color = Breed)) +
  geom_line()  +
  geom_point() +
  geom_label(aes(label = breed),
                   nudge_x = 1,
                   na.rm = TRUE) +
  theme(legend.position = "none")  +
  scale_y_continuous(breaks= c(1:10), trans = "reverse") +
  scale_x_continuous(breaks= c(2013:2020)) +
  ylab("") +
  xlab("") +
  xlim(c(2013,2022)) +
  scale_color_viridis(discrete = TRUE) +
  labs(
    title = "Popularity Rank of Breed\nbased on AKH registration",
    caption = "Tidy Tuesday Plot: @hardin47 | Data: Dog Breeds from AKH, contributor @KKakey")

Line plot with breed rank on the y-axis and year on the x-axis. Labrador Retrievers have ranked number 1 since 2013. Other reliably popular breeds include French Bulldogs, German Shepherds, Golden Retrievers, Bulldogs, Poodles, and Beagles.

praise()
## [1] "You are unreal!"

Practicing…

breed_traits %>%
  ggplot(aes(x = `Drooling Level`, y = `Affectionate With Family`)) + 
  geom_jitter(alpha = 0.2, width = 0.1, height = 0.1)