Skip to contents

Show Analysis: 24

Lukas Burk

2025-04-28

Source: vignettes/show-analysis-24.Rmd
show-analysis-24.Rmd

Use the search function to find the show you’re looking for. The show “24” is a particularly good example for a show with a bad name, because If we just search for “24”, we’ll get a wrong result due to ambiguity.
To nudge the search function to find the show we’re looking for, we can specify the year of release:

show_info <- search_query("24", years = 2001, type = "show")
show_info
#> # A tibble: 1 × 9
#>   type  score title  year trakt slug  tvdb  imdb      tmdb 
#>   <chr> <dbl> <chr> <int> <chr> <chr> <chr> <chr>     <chr>
#> 1 show   88.4 24     2001 1960  24    76290 tt0285331 1973

Now we have the basic show info to work with, including the title and various IDs.

Step 2: Use the ID

Use the trakt ID for subsequent API calls, which is guaranteed to be always available and unique on trakt.tv.
Now we’ll use seasons_summary() to get data for all seasons of the show, while also getting an additional list-column containing all episode data, which includes user ratings.

seasons <- seasons_summary(show_info$trakt, extended = "full", episodes = TRUE)
glimpse(seasons)
#> Rows: 9
#> Columns: 15
#> $ season         <int> 1, 2, 3, 4, 5, 6, 7, 8, 9
#> $ rating         <dbl> 8.16910, 8.18072, 8.13768, 8.22358, 8.47085, 7.45226, 7…
#> $ votes          <int> 479, 332, 276, 246, 223, 199, 186, 177, 197
#> $ episode_count  <int> 24, 24, 24, 24, 24, 24, 24, 24, 12
#> $ aired_episodes <int> 24, 24, 24, 24, 24, 24, 24, 24, 12
#> $ title          <chr> "Season 1", "Season 2", "Season 3", "Season 4", "Season…
#> $ overview       <chr> "Counter-terrorism agent Jack Bauer attempts to stop th…
#> $ first_aired    <dttm> 2001-11-07 02:00:00, 2002-10-30 02:00:00, 2003-10-29 02…
#> $ updated_at     <dttm> 2025-04-28 11:46:13, 2025-04-28 08:32:50, 2025-04-28 08…
#> $ network        <chr> "FOX", "FOX", "FOX", "FOX", "FOX", "FOX", "FOX", "FOX",…
#> $ original_title <chr> NA, NA, NA, NA, NA, NA, NA, NA, "Live Another Day"
#> $ episodes       <list> [<tbl_df[24 x 18]>], [<tbl_df[24 x 18]>], [<tbl_df[24 x…
#> $ trakt          <chr> "6262", "6263", "6264", "6265", "6266", "6267", "6268"…
#> $ tvdb           <chr> "10063", "10064", "10065", "10066", "10067", "16794", …
#> $ tmdb           <chr> "5845", "5846", "5847", "5848", "5849", "5850", "5851",…

Step 3: Tidying up

We’re interested in the $episodes list-column, which needs unnesting. In this case we can use dplyr::bind_rows() to take the list of tibbles and rbind them all together, meaning the result is a tibble of the episode data we care about.

episodes <- bind_rows(seasons$episodes)
glimpse(episodes)
#> Rows: 204
#> Columns: 18
#> $ season                 <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
#> $ episode                <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, …
#> $ title                  <chr> "12:00 A.M.-1:00 A.M.", "1:00 A.M.-2:00 A.M.", …
#> $ episode_abs            <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
#> $ overview               <chr> "Counter Terrorist Unit agent Jack Bauer is ass…
#> $ rating                 <dbl> 7.67248, 7.75382, 7.74105, 7.71981, 7.72116, 7.…
#> $ votes                  <int> 1606, 1243, 1089, 1060, 997, 954, 931, 927, 909…
#> $ comment_count          <int> 9, 4, 4, 3, 3, 4, 4, 2, 2, 3, 1, 3, 1, 2, 4, 5,…
#> $ first_aired            <dttm> 2001-11-07 02:00:00, 2001-11-14 02:00:00, 2001…
#> $ updated_at             <dttm> 2025-04-28 01:24:01, 2025-04-28 01:23:55, 2025…
#> $ available_translations <list> <"cs", "da", "de", "en", "es", "fr", "he", "hu…
#> $ runtime                <int> 43, 41, 43, 42, 42, 43, 43, 43, 43, 43, 43, 43,…
#> $ episode_type           <chr> "series_premiere", "standard", "standard", "sta…
#> $ original_title         <chr> "12:00 A.M.-1:00 A.M.", "1:00 A.M.-2:00 A.M.", …
#> $ trakt                  <chr> "146247", "146248", "146249", "146250", "146251…
#> $ tvdb                   <chr> "189255", "189256", "189257", "189258", "189259…
#> $ imdb                   <chr> "tt0502165", "tt0502167", "tt0502169", "tt05021…
#> $ tmdb                   <chr> "972745", "972752", "972753", "134397", "134398…

Step 4: Graph!

Now we have our episode data in a tidy form, might as well look at it.

ggplot(data = episodes, aes(x = episode, y = rating, color = votes)) +
  geom_point(size = 3, alpha = 2 / 3) +
  facet_wrap(~season, nrow = 1, scales = "free_x") +
  scale_x_continuous(breaks = c(1, 10, 20), expand = c(0, 3)) +
  scale_y_continuous(breaks = seq(0, 10, .5), minor_breaks = seq(0, 10, .25), limits = c(7, 9)) +
  scale_color_viridis_c() +
  guides(color = guide_colorbar(barwidth = unit(6, "cm"), title.vjust = .75)) +
  labs(
    title = "24: Episode Ratings on trakt.tv",
    subtitle = "Episode ratings by trakt.tv users by season",
    x = "Episode Number", y = "Rating (1-10)", color = "# of Votes",
    caption = "jemus42.github.io/tRakt"
  ) +
  theme_minimal() +
  theme(
    plot.title.position = "plot",
    legend.position = "bottom"
  )