A little late, but I decided to have a go at Tidy Tuesday with the recent Claremont Run dataset, looking at Chris Claremont’s 16 year run writing for the Uncanny X-men comic.
Looking at the
characters dataset provided, that describe some of the events that occur to each character in an issue, it seemed like being an X-Person was a pretty rough gig. I wondered, who got dealt the harshest hand during the entire Claremont run?
This also gave me a chance to (very slightly) play with the new
across (docs) function in the latest dplyr release. I’ve seen a few blog posts from excited R users around singing it’s praises, so it was good to at least touch it, even if I clearly haven’t made the most of it here.
I also played with
adorn_totals from the Janitor package for the first time, as well as adding an image to a plot with Cowplot’s
draw_image. Random new functions - always my favourite thing about working with R.
library(tidyverse) library(janitor) library(tidytuesdayR) library(ggthemr) library(cowplot) library(here) # set theme with ggthemr ggthemr('fresh') # import tidy tuesday data data <- tt_load(2020, week=27) characters <- data$characters # summarise total instances the state occurred on each character across run char_states_totals <- characters %>% select(-issue) %>% group_by(character) %>% summarise(across(is.numeric, sum)) %>% ungroup() %>% select(1:4, 6, 8) %>% janitor::adorn_totals("col", name = "total") %>% janitor::untabyl() %>% slice_max(total, n = 10) %>% select(character, total, everything()) %>% pivot_longer(3:7, names_to="state", values_to = "count") %>% separate(character, sep = " = ", into = c("codename", "name")) %>% mutate(codename = case_when(codename == "Ariel/Sprite/Shadowcat" ~ "Shadowcat", codename == "Marvel Girl/Phoenix" ~ "Jean Grey", TRUE ~ codename)) # create stacked column plot plot <- char_states_totals %>% mutate(state = str_replace_all(state, "_", " "), state = str_replace_all(state, "subject", "subjected"), state = str_to_sentence(state)) %>% mutate(state = fct_reorder(state, count), codename = fct_reorder(codename, total)) %>% ggplot(aes(codename, count, fill = state)) + geom_col() + coord_flip() + labs(title = "Which X-Men character had it worst?", subtitle = "During Chris Claremont's 1975-1991 run on Uncanny X-Men", x = "", y = "No. of Occurrences", fill = "") # add storm image to plot cowplot::ggdraw(plot) + cowplot::draw_image(here("xmen", "storm.jpg"), scale = .3, x = .37, y = .3)