The Richmond Way

library(tidyverse)
library(praise)

The Data

For Deepsha Menghani’s talk on Data Viz animation and interactivity in Quarto, she watched each episode of Ted Lasso at 2X speed and diligently noted down every F*bomb and gesture reference, and then made it into the richmondway R package!

richmondway <- read.csv("richmondway.csv") |>
  janitor::clean_names()

Exploring

richmondway |>
  ggplot(aes(x = episode_order, y = imdb_rating)) + 
  geom_point() +
  geom_vline(xintercept = 10.5, color = "blue") +
  geom_vline(xintercept = 22.5, color = "blue")

The first episode of the season is rated much lower than the last episode of the season for each of the three seasons (delineated by blue vertical lines).

Roy Kent

richmondway |>
  mutate(f_count_else = f_count_total - f_count_rk) |>
  pivot_longer(cols = c(`f_count_rk`,`f_count_else`), names_to = "who", values_to = "count") |>
  mutate(who = ifelse(who == "f_count_rk", "Roy Kent", "someone else")) |>
  mutate(count = ifelse(who == "Roy Kent", -count, count)) |>
  ggplot(aes(x = episode_order, y = count, fill = imdb_rating)) +
  geom_bar(stat = "identity", width = 0.8) +
  geom_hline(yintercept = 0, lwd = 1.5) + 
  geom_vline(xintercept = 10.5, color = "darkgrey", lwd = 0.5) + 
  geom_vline(xintercept = 22.5, color = "darkgrey", lwd = 0.5) +
  scale_x_reverse(limits = c(40, 0)) +  
  scale_y_continuous(breaks = seq(-25, 50, by = 5),
                     labels = as.character(c(seq(25, 0, by = -5), seq(5, 50, by = 5)))) +
  annotate("text", x = c(2, 13, 25), y = -21, label = c("Season 1", "Season 2", "Season 3")) +
  annotate("text", x = 39, y = c(-12.5, 14.5), label = c("F**k count, Roy Kent", "F**k count, everyone else"), color = "darkred", size = 5) + 
  coord_flip() +
  scale_fill_gradient(high = "red", low = "darkblue") + 
  labs(x = "", y = "",
       fill = "IMDB rating") +
  theme(axis.text.y = element_blank(), axis.ticks.y = element_blank())

F**k count for Roy Kent (left) vs other characters (right) on the TV show Ted Lasso. The color of the bar indicates the IMDB rating for the episode.

praise()

[1] "You are transcendent!"