The Mothership

Introduction

I would like to do a lot more with this, but currently time is scarce.
However, I want to fulfill Jason’s request, since I would love to be worthy of the title of record keeper.

Since its first episode on August 22, 2010, The Incomparable has accumulated 1155 hours of content (roughly 48 days) across 825 episodes.

The latest episode in the current dataset:

mothership_wide |>
  head(1) |>
  select(number, date, title, host, guest) |>
  mutate(
    date = as.Date(date),
    title = glue::glue("<a href=\"https://www.theincomparable.com/theincomparable/{number}\">{title}</a>"),
    guest = and::and(stringr::str_split(guest, ";", simplify = TRUE))
  ) |>
  knitr::kable(
    col.names = c("#", "Date", "Title", "Host", "Guests"),
    escape = FALSE
  ) |>
  kableExtra::kable_styling()

#	Date	Title	Host	Guests
812	2026-04-10	<a href="https://www.theincomparable.com/theincomparable/812">Ridley Scott Just Can't Stop</a>	Jason Snell	John Siracusa, Antony Johnston, Erika Ensign, and Moisés Chiullán

Panelists

2026 Panelists

There were 14 episodes published in 2026. Here’s a breakdown by host and guest counts.

mothership_long |>
  # Filter out special episodes containing letters
  filter(!str_detect(number, "[a-z]$"), year == current_year) |>
  count(person, role) |>
  pivot_wider(names_from = role, values_from = n, values_fill = 0) |>
  mutate(
    person = factor(person),
    total = guest + host,
    total_perc = scales::label_percent(.accuracy = .1)(total / nrow(mothership_wide)),
    rank = rank(-total, ties.method = "min")
  ) |>
  arrange(desc(total)) |>
  select(rank, person, host, guest, total, total_perc) |>
  reactable(
    columns = list(
      rank = colDef(name = "Rank", sortable = TRUE),
      person = colDef(name = "Person", filterable = TRUE, sortable = TRUE),
      host = colDef(name = "Host", sortable = TRUE),
      guest = colDef(name = "Guest", sortable = TRUE),
      total = colDef(name = "Total", sortable = TRUE),
      total_perc = colDef(name = "Total (%)", sortable = TRUE)
    )
  )

Looking at it as a bar chart is not really helping I guess but sure why not.

panelist_breakdown <- mothership_long |>
  filter(year == current_year) |>
  group_by(person, role) |>
  tally() |>
  spread(role, n) |>
  replace_na(list(guest = 0, host = 0)) |>
  mutate(total = guest + host)

panelist_breakdown_long <- panelist_breakdown |>
  gather(role, n, guest, host) 


ggplot(data = panelist_breakdown_long, aes(x = reorder(person, total), y = n, fill = role)) +
  geom_col(color = "black", alpha = .6) +
  coord_flip() +
  scale_y_continuous(breaks = seq(0, 100, 5), minor_breaks = seq(0, 100, 1)) +
  scale_fill_brewer(palette = "Dark2", label = c("Guest", "Host")) +
  labs(
    title = glue::glue("The Incomparable — {current_year}"),
    subtitle = "Panelists by # of Appearances",
    x = "Panelist", y = "# of Appearances", fill = "Role"
  )

All Time Stats

Here are some rankings of panelists (including hosts) across different metrics / subsets.
Special bonus episodes are not included (507b, 506b, 337b, 173z).

By Number of Appearances

Nothing special, just “appears in episode” counts.

mothership_long |>
  # Filter out special episodes containing letters
  filter(!str_detect(number, "[a-z]$")) |>
  count(person, role) |>
  pivot_wider(names_from = role, values_from = n, values_fill = 0) |>
  mutate(
    person = factor(person),
    total = guest + host,
    total_perc = scales::label_percent(.accuracy = .1)(total / nrow(mothership_wide)),
    rank = rank(-total, ties.method = "min")
  ) |>
  arrange(desc(total)) |>
  select(rank, person, host, guest, total, total_perc) |>
  reactable(
    columns = list(
      rank = colDef(name = "Rank", sortable = TRUE),
      person = colDef(name = "Person", filterable = TRUE, sortable = TRUE),
      host = colDef(name = "Host", sortable = TRUE),
      guest = colDef(name = "Guest", sortable = TRUE),
      total = colDef(name = "Total", sortable = TRUE),
      total_perc = colDef(name = "Total (%)", sortable = TRUE)
    )
  )

By Duration of Appearance

Duration per episode in which each person appears, one episode can count towards multiple people’s total of course.

mothership_long |>
  # Filter out special episodes containing letters
  filter(!str_detect(number, "[a-z]$")) |>
  group_by(person) |>
  summarize(mins = sum(as.numeric(duration)/60)) |>
  mutate(
    mins = round(mins, 1),
    hours = round(mins/60, 1), 
    days = round(hours/24, 1),
    person = factor(person),
    runtime_perc = scales::label_percent(accuracy = .1)(mins / sum(as.numeric(mothership_wide$duration/60))),
    rank = rank(-mins, ties.method = "min")
  ) |>
  arrange(rank) |>
  select(rank, person, runtime_perc, mins, hours, days) |>
  reactable(
    columns = list(
      rank = colDef(name = "Rank", sortable = TRUE),
      person = colDef(name = "Person", filterable = TRUE, sortable = TRUE),
      runtime_perc = colDef(name = "% of All", sortable = TRUE),
      mins = colDef(name = "Minutes", sortable = TRUE),
      hours = colDef(name = "Hours", sortable = TRUE),
      days = colDef(name = "Days", sortable = TRUE)
    )
  )

Runtime

Because that’s the easy one.

# column: screen-inset-shaded
tmp <- mothership_wide |>
  mutate(title_long = str_wrap(paste0(number, ": ", title), 20))

ggplot(tmp, aes(x = date, y = duration)) +
  geom_point(alpha = .75) +
  geom_smooth(method = loess, formula = y ~ x, se = FALSE, color = "red") +
  geom_label_repel(
    data = slice_max(tmp, duration, n = 8),
    aes(label = title_long), alpha = .8, size = 3
  ) +
  scale_x_date(
    date_breaks = "1 year", date_labels = "%Y"
  ) +
  scale_y_time(
    breaks = hms(minutes = seq(0, 1e5, 60)),
    limits = c(0, NA)
  ) +
  labs(
    title = "The Incomparable: Mothership",
    subtitle = "Episode runtimes",
    y = "Duration (HH:MM:SS)", x = "Date Published",
    caption = caption
  )

By Year

# column: screen-inset-shaded
mothership_wide |> 
  ggplot(aes(x = factor(year), y = duration)) +
    geom_point(
      alpha = .75,
      position = position_jitter(height = 0, width = .2)
    ) +
    geom_boxplot(outlier.alpha = 0, alpha = .5) +
    stat_summary(fun = mean, geom = "point", color = "red") +
    scale_y_time(
      breaks = hms(minutes = seq(0, 1e5, 60)),
      limits = c(0, NA)
    ) +
    labs(
      title = "The Incomparable Network: Mothership",
      subtitle = "Episode runtimes",
      y = "Duration (HH:MM:SS)", x = "Year Published",
      caption = caption
    )

Per Person

# column: screen-inset-shaded
mothership_long |>
  filter(year >= 2011) |>
  group_by(person) |>
  mutate(mean_duration = mean(duration)) |>
  ggplot(aes(x = reorder(person, mean_duration), y = duration)) +
  geom_point(alpha = .5, position = position_jitter(height = 0, width = .25)) +
  geom_boxplot(alpha = .5, outlier.alpha = 0) +
  coord_flip() +
  labs(
    title = "The Incomparable Mothership",
    subtitle = "Episode runtimes by panelist",
    y = "Duration (HH:MM:SS)", x = "Panelist",
    caption = caption
  )