596 episodes. 40 seasons. 1 package!
survivoR is a collection of data sets detailing events across all 40 seasons of the US Survivor, including castaway information, vote history, immunity and reward challenge winners and jury votes.
Now on CRAN.
install.packages("survivoR")Or install from Git for the latest.
devtools::install_github("doehm/survivoR")A table containing summary details of each season of Survivor, including the winner, runner ups and location. Note this is a nested data frame given there may be 1 or 2 runner ups. The grain is maintained to 1 row per season.
season_summary
#> # A tibble: 40 x 19
#> season_name season location country tribe_setup full_name winner runner_ups
#> <chr> <int> <chr> <chr> <chr> <glue> <chr> <chr>
#> 1 Survivor: B~ 1 Pulau Ti~ Malays~ Two tribes~ Richard ~ Richa~ Kelly Wig~
#> 2 Survivor: T~ 2 Herbert ~ Austra~ Two tribes~ Tina Wes~ Tina Colby Don~
#> 3 Survivor: A~ 3 Shaba Na~ Kenya Two tribes~ Ethan Zo~ Ethan Kim Johns~
#> 4 Survivor: M~ 4 Nuku Hiv~ Polyne~ Two tribes~ Vecepia ~ Vecep~ Neleh Den~
#> 5 Survivor: T~ 5 Ko Tarut~ Thaila~ Two tribes~ Brian He~ Brian Clay Jord~
#> 6 Survivor: T~ 6 Rio Negr~ Brazil Two tribes~ Jenna Mo~ Jenna Matthew V~
#> 7 Survivor: P~ 7 Pearl Is~ Panama Two tribes~ Sandra D~ Sandra Lillian M~
#> 8 Survivor: A~ 8 Pearl Is~ Panama Three trib~ Amber Br~ Amber Rob Maria~
#> 9 Survivor: V~ 9 Efate, S~ Vanuatu Two tribes~ Chris Da~ Chris Twila Tan~
#> 10 Survivor: P~ 10 Koror, P~ Palau A schoolya~ Tom West~ Tom Katie Gal~
#> # ... with 30 more rows, and 11 more variables: final_vote <chr>,
#> # timeslot <chr>, premiered <date>, ended <date>, filming_started <date>,
#> # filming_ended <date>, viewers_premier <dbl>, viewers_finale <dbl>,
#> # viewers_reunion <dbl>, viewers_mean <dbl>, rank <dbl>season_summary %>%
select(season, viewers_premier, viewers_finale, viewers_reunion, viewers_mean) %>%
pivot_longer(cols = -season, names_to = "episode", values_to = "viewers") %>%
mutate(
episode = to_title_case(str_replace(episode, "viewers_", ""))
) %>%
ggplot(aes(x = season, y = viewers, colour = episode)) +
geom_line() +
geom_point(size = 2) +
theme_minimal() +
scale_colour_tribes(16) +
labs(
title = "Survivor viewers over the 40 seasons",
x = "Season",
y = "Viewers (Millions)",
colour = "Episode"
)
Season and demographic information about each castaway. Within a season
the data is ordered by the first voted out, to sole survivor indicated
by order. When demographic information is missing, it
likely means that the castaway re-entered the game at a later stage by
winning the opportunity to return. Also meaning the castaway will
feature in the data twice for the season. Castaways that have played in
multiple seasons will feature more than once with the age and location
representing that point in time.
castaways %>%
filter(season == 40)
#> # A tibble: 22 x 18
#> season_name season full_name castaway age city state personality_type
#> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr> <chr>
#> 1 Survivor: Wi~ 40 Natalie An~ Natalie 33 Edge~ New J~ ESTP
#> 2 Survivor: Wi~ 40 Amber Mari~ Amber 40 Pens~ Flori~ ISFP
#> 3 Survivor: Wi~ 40 Danni Boat~ Danni 43 Shaw~ Kansas ENFJ
#> 4 Survivor: Wi~ 40 Ethan Zohn Ethan 45 Hill~ New H~ ISFP
#> 5 Survivor: Wi~ 40 Tyson Apos~ Tyson 39 Mesa Arizo~ ESTP
#> 6 Survivor: Wi~ 40 Rob Mariano Rob 43 Pens~ Flori~ ESTJ
#> 7 Survivor: Wi~ 40 Parvati Sh~ Parvati 36 Los ~ Calif~ ENFJ
#> 8 Survivor: Wi~ 40 Sandra Dia~ Sandra 44 Rive~ Flori~ ESTP
#> 9 Survivor: Wi~ 40 Yul Kwon Yul 44 Los ~ Calif~ INTJ
#> 10 Survivor: Wi~ 40 Wendell Ho~ Wendell 35 Phil~ Penns~ INFJ
#> # ... with 12 more rows, and 10 more variables: day <dbl>, order <int>,
#> # result <chr>, jury_status <chr>, original_tribe <chr>, swapped_tribe <chr>,
#> # swapped_tribe2 <chr>, merged_tribe <chr>, total_votes_received <dbl>,
#> # immunity_idols_won <dbl>This data frame contains a complete history of votes cast across all seasons of Survivor. This allows you to see who who voted for who at which Tribal Council. It also includes details on who had individual immunity as well as who had their votes nullified by a hidden immunity idol. This details the key events for the season.
vh <- vote_history %>%
filter(
season == 40,
episode == 10
)
vh
#> # A tibble: 11 x 12
#> season_name season episode day tribe_status castaway immunity vote
#> <chr> <dbl> <dbl> <dbl> <chr> <chr> <chr> <chr>
#> 1 Survivor: Winners~ 40 10 25 merged Ben <NA> Tyson
#> 2 Survivor: Winners~ 40 10 25 merged Denise hidden None
#> 3 Survivor: Winners~ 40 10 25 merged Jeremy <NA> Immu~
#> 4 Survivor: Winners~ 40 10 25 merged Kim <NA> Soph~
#> 5 Survivor: Winners~ 40 10 25 merged Michele <NA> Tyson
#> 6 Survivor: Winners~ 40 10 25 merged Nick <NA> Tyson
#> 7 Survivor: Winners~ 40 10 25 merged Sarah <NA> Deni~
#> 8 Survivor: Winners~ 40 10 25 merged Sarah <NA> Tyson
#> 9 Survivor: Winners~ 40 10 25 merged Sophie <NA> Deni~
#> 10 Survivor: Winners~ 40 10 25 merged Tony individu~ Tyson
#> 11 Survivor: Winners~ 40 10 25 merged Tyson <NA> Soph~
#> # ... with 4 more variables: nullified <lgl>, voted_out <chr>, order <dbl>,
#> # vote_order <dbl>vh %>%
count(vote)
#> # A tibble: 5 x 2
#> vote n
#> <chr> <int>
#> 1 Denise 2
#> 2 Immune 1
#> 3 None 1
#> 4 Sophie 2
#> 5 Tyson 5Events in the game such as fire challenges, rock draws, steal-a-vote
advantages or countbacks in the early days often mean a vote wasn’t
placed for an individual. Rather a challenge may be won, lost, no vote
cast but attended Tribal Council, etc. These events are recorded in the
vote field. I have included a function
clean_votes for when only need the votes cast for
individuals. If the input data frame has the vote column it
can simply be piped.
vh %>%
clean_votes() %>%
count(vote)
#> # A tibble: 3 x 2
#> vote n
#> <chr> <int>
#> 1 Denise 2
#> 2 Sophie 2
#> 3 Tyson 5A nested tidy data frame of immunity and reward challenge results. The
winners and winning tribe of the challenge are found by expanding the
winners column. For individual immunity challenges the winning tribe
is simply NA.
challenges %>%
filter(season == 40)
#> # A tibble: 28 x 7
#> season_name season episode title day challenge_type winners
#> <chr> <dbl> <dbl> <chr> <dbl> <chr> <list>
#> 1 Survivor: Winne~ 40 1 Greatest of~ 2 reward <tibble[,2~
#> 2 Survivor: Winne~ 40 1 Greatest of~ 2 immunity <tibble[,2~
#> 3 Survivor: Winne~ 40 1 Greatest of~ 3 immunity <tibble[,2~
#> 4 Survivor: Winne~ 40 2 It's Like a~ 6 reward <tibble[,2~
#> 5 Survivor: Winne~ 40 2 It's Like a~ 6 immunity <tibble[,2~
#> 6 Survivor: Winne~ 40 3 Out for Blo~ 9 reward <tibble[,2~
#> 7 Survivor: Winne~ 40 3 Out for Blo~ 9 immunity <tibble[,2~
#> 8 Survivor: Winne~ 40 4 I Like Reve~ 11 reward <tibble[,2~
#> 9 Survivor: Winne~ 40 4 I Like Reve~ 11 immunity <tibble[,2~
#> 10 Survivor: Winne~ 40 5 The Buddy S~ 14 immunity <tibble[,2~
#> # ... with 18 more rowsTypically in the merge if a single person win a reward they are allowed to bring others along with them. The first castaway in the expanded list is likely to be the winner and the subsequent players those they brought along with them. Although, not always. Occasionally in the merge the castaways are split into two teams for the purpose of the reward, in which case all castaways win the reward rather than a single person.
The day field on this data set represents the day of the tribal
council rather than the day of the challenge. This is to more easily
associate the reward challenge with the immunity challenge and result of
the tribal council. It also helps for joining tables.
Note the challenges table is the combined immunity and rewards tables which will eventually be dropped in later releases.
History of jury votes. It is more verbose than it needs to be, however having a 0-1 column indicating if a vote was placed or not makes it easier to summarise castaways that received no votes.
jury_votes %>%
filter(season == 40)
#> # A tibble: 48 x 5
#> season_name season castaway finalist vote
#> <chr> <dbl> <chr> <chr> <dbl>
#> 1 Survivor: Winners at War 40 Sarah Michele 0
#> 2 Survivor: Winners at War 40 Sarah Natalie 0
#> 3 Survivor: Winners at War 40 Sarah Tony 1
#> 4 Survivor: Winners at War 40 Ben Michele 0
#> 5 Survivor: Winners at War 40 Ben Natalie 0
#> 6 Survivor: Winners at War 40 Ben Tony 1
#> 7 Survivor: Winners at War 40 Denise Michele 0
#> 8 Survivor: Winners at War 40 Denise Natalie 0
#> 9 Survivor: Winners at War 40 Denise Tony 1
#> 10 Survivor: Winners at War 40 Nick Michele 0
#> # ... with 38 more rowsjury_votes %>%
filter(season == 40) %>%
group_by(finalist) %>%
summarise(votes = sum(vote))
#> # A tibble: 3 x 2
#> finalist votes
#> <chr> <dbl>
#> 1 Michele 0
#> 2 Natalie 4
#> 3 Tony 12Hidden Idols
A dataset containing the history of hidden immunity idols including who found them, on what day and which day they were played. The idol number increments for each idol the castaway finds during the game.
hidden_idols %>%
filter(season == 40)
#> # A tibble: 10 x 9
#> season_name season castaway idol_number idols_held votes_nullified day_found
#> <chr> <dbl> <chr> <chr> <dbl> <chr> <dbl>
#> 1 Survivor: W~ 40 Sandra ~ 1 1 <NA> 3
#> 2 Survivor: W~ 40 Denise ~ 1 1 0 4
#> 3 Survivor: W~ 40 Kim Spr~ 1 1 2 4
#> 4 Survivor: W~ 40 Sophie ~ 1 1 <NA> 12
#> 5 Survivor: W~ 40 Denise ~ 2 1 4 16
#> 6 Survivor: W~ 40 Michele~ 1 1 2 22
#> 7 Survivor: W~ 40 Tony Vl~ 1 1 0 28
#> 8 Survivor: W~ 40 Ben Dri~ 1 1 2 29
#> 9 Survivor: W~ 40 Natalie~ 1 1 4 35
#> 10 Survivor: W~ 40 Natalie~ 2 1 0 37
#> # ... with 2 more variables: day_played <dbl>, legacy_advantage <lgl>A data frame containing the viewer information for every episode across all sesasons. It also includes the rating and viewer share information for viewers aged 18 to 49 years of age.
viewers %>%
filter(season == 40)
#> # A tibble: 14 x 9
#> season_name season episode_number_~ episode title episode_date viewers
#> <chr> <dbl> <dbl> <dbl> <chr> <date> <dbl>
#> 1 Survivor: Win~ 40 583 1 Greatest~ 2020-02-12 6.68
#> 2 Survivor: Win~ 40 584 2 It's Lik~ 2020-02-19 7.16
#> 3 Survivor: Win~ 40 585 3 Out for ~ 2020-02-26 7.14
#> 4 Survivor: Win~ 40 586 4 I Like R~ 2020-03-04 7.08
#> 5 Survivor: Win~ 40 587 5 The Budd~ 2020-03-11 6.91
#> 6 Survivor: Win~ 40 588 6 Quick on~ 2020-03-18 7.83
#> 7 Survivor: Win~ 40 589 7 We're in~ 2020-03-25 8.18
#> 8 Survivor: Win~ 40 590 8 This is ~ 2020-04-01 8.23
#> 9 Survivor: Win~ 40 591 9 War is N~ 2020-04-08 7.85
#> 10 Survivor: Win~ 40 592 10 The Full~ 2020-04-15 8.14
#> 11 Survivor: Win~ 40 593 11 This is ~ 2020-04-22 8.16
#> 12 Survivor: Win~ 40 594 12 Friendly~ 2020-04-29 8.08
#> 13 Survivor: Win~ 40 595 13 The Penu~ 2020-05-06 7.57
#> 14 Survivor: Win~ 40 596 14 It All B~ 2020-05-13 7.94
#> # ... with 2 more variables: rating_18_49 <dbl>, share_18_49 <dbl>This data frame contains the tribe names and colours for each season, including the RGB values. These colours can be joined with the other data frames to customise colours for plots. Another option is to add tribal colours to ggplots with the scale functions.
tribe_colours
#> # A tibble: 139 x 5
#> # Groups: season, tribe [139]
#> season_name season tribe tribe_colour tribe_status
#> <chr> <dbl> <chr> <chr> <chr>
#> 1 Survivor: Winners at War 40 Koru #000000 merged
#> 2 Survivor: Winners at War 40 Dakal #D80E0E original
#> 3 Survivor: Winners at War 40 Sele #0067D6 original
#> 4 Survivor: Winners at War 40 Yara #049451 swapped
#> 5 Survivor: Island of the Idols 39 Lumuwaku #304ED2 merged
#> 6 Survivor: Island of the Idols 39 Lairo #F39442 original
#> 7 Survivor: Island of the Idols 39 Vokai #D99CD3 original
#> 8 Survivor: Edge of Extinction 38 Vata #D32323 merged
#> 9 Survivor: Edge of Extinction 38 Kama #FACF22 original
#> 10 Survivor: Edge of Extinction 38 Manu #1050BA original
#> # ... with 129 more rows
Included are ggplot2 scale functions of the form
scale_fill_survivor() and
scale_fill_tribes() to add season and tribe colours to
ggplot. The scale_fill_survivor() scales uses a colour
palette extracted from the season logo and
scale_fill_tribes() scales uses the tribal colours of the
specified season as a colour palette.
All that is required for the ‘survivor’ palettes is the desired season as input. If not season is provided it will default to season 40.
castaways %>%
count(season, personality_type) %>%
ggplot(aes(x = season, y = n, fill = personality_type)) +
geom_bar(stat = "identity") +
scale_fill_survivor(40) +
theme_minimal()
Below are the palettes for all seasons.
To use the tribe scales, simply input the season number desired to use
those tribe colours. If the fill or colour aesthetic is the tribe name,
this needs to be passed to the scale function as
scale_fill_tribes(season, tribe = tribe) (for now) where
tribe is on the input data frame. If the fill or colour
aesthetic is independent from the actual tribe names, like gender for
example, tribe does not need to be specified and will
simply use the tribe colours as a colour palette, such as the viewers
line graph above.
ssn <- 35
labels <- castaways %>%
filter(
season == ssn,
str_detect(result, "Sole|unner")
) %>%
mutate(label = glue("{castaway} ({original_tribe})")) %>%
select(label, castaway)
jury_votes %>%
filter(season == ssn) %>%
left_join(
castaways %>%
filter(season == ssn) %>%
select(castaway, original_tribe),
by = "castaway"
) %>%
group_by(finalist, original_tribe) %>%
summarise(votes = sum(vote)) %>%
left_join(labels, by = c("finalist" = "castaway")) %>%
{
ggplot(., aes(x = label, y = votes, fill = original_tribe)) +
geom_bar(stat = "identity", width = 0.5) +
scale_fill_tribes(ssn, tribe = .$original_tribe) +
theme_minimal() +
labs(
x = "Finalist (original tribe)",
y = "Votes",
fill = "Original\ntribe",
title = "Votes received by each finalist"
)
}
Given the variable nature of the game of Survivor and changing of the rules, there are bound to be edges cases where the data is not quite right. Please log an issue and I will correct the datasets.
New features will be added, such as details on exiled castaways across the seasons. If you have a request for specific data let me know in the issues and I’ll see what I can do. Also, if you’d like to contribute by adding to existing datasets or contribute a new dataset, please contact me directly.
Data viz projects to showcase the data sets. This looks at the number of immunity idols won and votes received for each winner.
A big thank you to:
- Camilla Bendetti for collating the personality type data for each castaway.
- Uygar Sozer for adding the filming start and end dates for each season.
Data was almost entirely sourced from Wikipedia. Other data, such as the tribe colours, was manually recorded and entered by myself and contributors.
Torch graphic in hex: Fire Torch Vectors by Vecteezy