Note: I reordered some sections
scooby <- read_excel("../00_data/MyData.xlsx")
scrappy <- scooby %>%
select(monster_type, series_name, title, run_time, imdb) %>%
filter(monster_type %in% c("Mechanical"))scrappy_wide <- scrappy %>%
pivot_wider(names_from = imdb,
values_from = run_time)
scrappy_wide## # A tibble: 15 × 13
## monster_type series_name title `8.2` `7.1` `7.7` `7.6` `8.7` `6.5` `7.5`
## <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Mechanical Scooby Doo, Whe… Foul… 21 NA NA NA NA NA NA
## 2 Mechanical Scooby-Doo and … Robo… NA 8 NA NA NA NA NA
## 3 Mechanical Scooby-Doo and … Scoo… NA 8 NA NA NA NA NA
## 4 Mechanical A Pup Named Sco… The … NA NA 23 NA NA NA NA
## 5 Mechanical What's New Scoo… A Te… NA NA NA 21 NA NA NA
## 6 Mechanical Scooby-Doo Myst… Howl… 23 NA NA NA NA NA NA
## 7 Mechanical Scooby-Doo Myst… Art … NA NA 23 NA NA NA NA
## 8 Mechanical Scooby-Doo Myst… Hear… NA NA NA 22 NA NA NA
## 9 Mechanical Scooby-Doo Myst… Gate… NA NA NA NA 23 NA NA
## 10 Mechanical Warner Home Vid… Scoo… NA NA NA NA NA 23 NA
## 11 Mechanical Be Cool, Scooby… Me, … NA NA NA NA NA NA 22
## 12 Mechanical Be Cool, Scooby… Junk… NA NA NA NA NA NA NA
## 13 Mechanical Be Cool, Scooby… Pizz… NA NA NA NA NA NA NA
## 14 Mechanical Scooby-Doo and … The … NA NA NA NA NA NA NA
## 15 Mechanical Scooby-Doo and … Tota… NA NA NA NA NA NA NA
## # ℹ 3 more variables: `6.9` <dbl>, `6.8` <dbl>, `NA` <dbl>scrappy_long <- scrappy_wide %>%
pivot_longer(cols = c(`8.2`, `7.1`, `7.7`, `7.6`, `8.7`, `6.9`, `6.8`, `NA`, `6.5`, `7.5`),
names_to = "imdb",
values_to = "run_time")
scrappy_long## # A tibble: 150 × 5
## monster_type series_name title imdb run_time
## <chr> <chr> <chr> <chr> <dbl>
## 1 Mechanical Scooby Doo, Where Are You! Foul Play in Funland 8.2 21
## 2 Mechanical Scooby Doo, Where Are You! Foul Play in Funland 7.1 NA
## 3 Mechanical Scooby Doo, Where Are You! Foul Play in Funland 7.7 NA
## 4 Mechanical Scooby Doo, Where Are You! Foul Play in Funland 7.6 NA
## 5 Mechanical Scooby Doo, Where Are You! Foul Play in Funland 8.7 NA
## 6 Mechanical Scooby Doo, Where Are You! Foul Play in Funland 6.9 NA
## 7 Mechanical Scooby Doo, Where Are You! Foul Play in Funland 6.8 NA
## 8 Mechanical Scooby Doo, Where Are You! Foul Play in Funland NA NA
## 9 Mechanical Scooby Doo, Where Are You! Foul Play in Funland 6.5 NA
## 10 Mechanical Scooby Doo, Where Are You! Foul Play in Funland 7.5 NA
## # ℹ 140 more rowshexgirls <- scooby %>%
select(title, monster_real, monster_amount, suspects_amount, series_name) %>%
filter(monster_real %in% c("FALSE", "TRUE"),
series_name %in% c("Warner Home Video"))
hexgirls## # A tibble: 41 × 5
## title monster_real monster_amount suspects_amount series_name
## <chr> <chr> <dbl> <dbl> <chr>
## 1 Scooby-Doo on Zombie… TRUE 7 6 Warner Hom…
## 2 Scooby-Doo and the W… TRUE 5 4 Warner Hom…
## 3 Scooby-Doo and the A… FALSE 3 10 Warner Hom…
## 4 Scooby-Doo and the C… TRUE 1 4 Warner Hom…
## 5 Scooby-Doo! and the … FALSE 4 10 Warner Hom…
## 6 Scooby-Doo! and the … FALSE 7 9 Warner Hom…
## 7 Scooby-Doo! and the … FALSE 2 8 Warner Hom…
## 8 Aloha, Scooby-Doo! FALSE 2 7 Warner Hom…
## 9 Scooby-Doo! in Where… FALSE 3 7 Warner Hom…
## 10 Scooby-Doo! Pirates … FALSE 4 5 Warner Hom…
## # ℹ 31 more rowshexgirls_united <- hexgirls %>%
unite(col = "monstervsuspect", c(monster_amount,suspects_amount), sep = "/", )
hexgirls_united## # A tibble: 41 × 4
## title monster_real monstervsuspect series_name
## <chr> <chr> <chr> <chr>
## 1 Scooby-Doo on Zombie Island TRUE 7/6 Warner Hom…
## 2 Scooby-Doo and the Witch's Ghost TRUE 5/4 Warner Hom…
## 3 Scooby-Doo and the Alien Invaders FALSE 3/10 Warner Hom…
## 4 Scooby-Doo and the Cyber Chase TRUE 1/4 Warner Hom…
## 5 Scooby-Doo! and the Legend of the V… FALSE 4/10 Warner Hom…
## 6 Scooby-Doo! and the Monster of Mexi… FALSE 7/9 Warner Hom…
## 7 Scooby-Doo! and the Loch Ness Monst… FALSE 2/8 Warner Hom…
## 8 Aloha, Scooby-Doo! FALSE 2/7 Warner Hom…
## 9 Scooby-Doo! in Where's my Mummy? FALSE 3/7 Warner Hom…
## 10 Scooby-Doo! Pirates Ahoy! FALSE 4/5 Warner Hom…
## # ℹ 31 more rowshexgirls_seperated <- hexgirls_united %>%
separate(col = monstervsuspect, into = c("monster_amount", "suspects_amount"))
hexgirls_seperated## # A tibble: 41 × 5
## title monster_real monster_amount suspects_amount series_name
## <chr> <chr> <chr> <chr> <chr>
## 1 Scooby-Doo on Zombie… TRUE 7 6 Warner Hom…
## 2 Scooby-Doo and the W… TRUE 5 4 Warner Hom…
## 3 Scooby-Doo and the A… FALSE 3 10 Warner Hom…
## 4 Scooby-Doo and the C… TRUE 1 4 Warner Hom…
## 5 Scooby-Doo! and the … FALSE 4 10 Warner Hom…
## 6 Scooby-Doo! and the … FALSE 7 9 Warner Hom…
## 7 Scooby-Doo! and the … FALSE 2 8 Warner Hom…
## 8 Aloha, Scooby-Doo! FALSE 2 7 Warner Hom…
## 9 Scooby-Doo! in Where… FALSE 3 7 Warner Hom…
## 10 Scooby-Doo! Pirates … FALSE 4 5 Warner Hom…
## # ℹ 31 more rows