I design tools that promote animal health and welfare in the zoo and agricultural industries.
Today’s TidyTuesday is all about anime characters. Our R Users Group worked on it. Beer was involved.
library(tidyverse)
tidy_anime <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-04-23/tidy_anime.csv")
my_anime <- tidy_anime %>%
select(animeID, name, score, scored_by, start_date, rating) %>%
unique() %>%
filter(scored_by > 30) %>%
mutate(
smutlevel = case_when(
rating == "None" ~ 0,
rating == "G - All Ages" ~ 1,
rating == "PG - Children" ~ 2,
rating == "PG-13 - Teens 13 or older" ~ 3,
rating == "R - 17+ (violence & profanity)" ~ 4,
rating == "R+ - Mild Nudity" ~ 5
),
smutlevel_letter = gsub(" -.*", "", smutlevel)
)
ggplot(my_anime, aes(x = score)) +
geom_histogram()
my_anime %>%
ggplot(aes(x = rating, y = score)) +
#geom_jitter(alpha = 0.1) +
geom_violin() +
geom_jitter(alpha = 0.1) +
scale_x_discrete(
limits = c(
"None",
"G - All Ages",
"PG - Children",
"PG-13 - Teens 13 or older",
"R - 17+ (violence & profanity)",
"R+ - Mild Nudity"
)
)
my_anime %>%
ggplot(aes(y = score)) +
geom_violin(aes(x = as.factor(smutlevel))) +
geom_smooth(aes(x = smutlevel + 1), method = "loess") +
#scale_x_discrete(labels = c("None", "G - All Ages", "PG - Children", "PG-13 - Teens 13 or older", "R - 17+ (violence & profanity)", "R+ - Mild Nudity"))
scale_x_discrete(labels = c("NA", "G", "PG", "PG13", "R", "R+")) +
labs(
x = "Smut Level",
y = "Score",
title = "Smut level in Anime vs. Readers' scores",
subtitle = "Popcorn Freaks"
)
cor(my_anime$smutlevel, my_anime$score)
## [1] 0.3296361