1 Prerequisites

1.1 Materials

Please visit https://github.com/arifpras/KelasData for the datasets and other relevant materials to be used during the sessions.

1.2 Clearing the environment

rm(list=ls())
ls()
## character(0)

1.3 Packages and libraries

#which directory at the moment
getwd()
## [1] "/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/WranglingViz"
#setting working directory
setwd("/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/KelasData")

#dir()

1.4 Datasets

#sources:
##--https://www.kaggle.com/michau96
##--https://www.kaggle.com/aditya2803
##--https://www.opfanpage.com/2018/06/29/one-piece-power-ranking-chart/
##--https://listfist.com/list-of-one-piece-characters-by-age

#".csv" files - local

#op_chapters <- read.csv(file.choose())
#op_chapters <- read.csv("/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/KelasData/00_Datasets/OP_chapters.csv")

#op_characters <- read.csv(file.choose())
#op_characters <- read.csv("/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/KelasData/00_Datasets/OP_characters.csv")

#op_ratings <- read.csv(file.choose())
#op_ratings <- read.csv("/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/KelasData/00_Datasets/OP_ratings.csv")

#op_powers <- read.csv(file.choose())
#op_powers <- read.csv("/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/KelasData/00_Datasets/OP_powers.csv")

#op_ages <- read.csv(file.choose())
#op_ages <- read.csv("/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/KelasData/00_Datasets/OP_ages.csv")

#".xlsx" files - local
#op_chapters <- read_excel(path = "/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/KelasData/00_Datasets/OP_all.xlsx", sheet = "OP_chapters")
#op_characters <- read_excel(path = "/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/KelasData/00_Datasets/OP_all.xlsx", sheet = "OP_characters")
#op_ratings <- read_excel(path = "/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/KelasData/00_Datasets/OP_all.xlsx", sheet = "OP_ratings")
op_powers <- readxl::read_excel(path = "/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/KelasData/00_Datasets/OP_all.xlsx", sheet = 4)
op_ages <- read_excel(path = "/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/KelasData/00_Datasets/OP_all.xlsx", sheet = "OP_ages")

#".csv" files - cloud
#op_chapters <- read.csv("https://www.dropbox.com/s/t1vrxsa4ad0m2c4/OP_chapters.csv?dl=1")
#op_characters <- read.csv("https://www.dropbox.com/s/e74njw4iw7qfzbl/OP_characters.csv?dl=1")
#op_ratings <- read.csv("https://www.dropbox.com/s/qvdhlnkyk02giuj/OP_ratings.csv?dl=1")
#op_powers <- read.csv("https://www.dropbox.com/s/t3gbzzscz438ecp/OP_powers.csv?dl=1")
#op_ages <- read.csv("https://www.dropbox.com/s/r24vzv7eyz35irr/OP_ages.csv?dl=1")

#require(devtools)
#install_github("Displayr/flipAPI")
#library(flipAPI)

#".xlsx" files - cloud
#op_chapters <- flipAPI::DownloadXLSX("https://www.dropbox.com/s/5mev3xo0cd3tc61/OP_all.xlsx?dl=0", sheet = 1)
#op_characters <- flipAPI::DownloadXLSX("https://www.dropbox.com/s/5mev3xo0cd3tc61/OP_all.xlsx?dl=0", sheet = "OP_characters")
#op_ratings <- flipAPI::DownloadXLSX("https://www.dropbox.com/s/5mev3xo0cd3tc61/OP_all.xlsx?dl=0", sheet = 3)
#op_powers <- flipAPI::DownloadXLSX("https://www.dropbox.com/s/5mev3xo0cd3tc61/OP_all.xlsx?dl=0", sheet = "OP_powers", want.data.frame = TRUE)
#op_ages <- flipAPI::DownloadXLSX("https://www.dropbox.com/s/5mev3xo0cd3tc61/OP_all.xlsx?dl=0", sheet = "OP_ages", want.data.frame = TRUE)
str(op_powers)
## tibble [56 × 4] (S3: tbl_df/tbl/data.frame)
##  $ power       : num [1:56] 100 100 100 100 99 95 95 94.5 94 93 ...
##  $ character   : chr [1:56] "Red Haired Shanks" "Marshall D. Teach" "Charlotte Linlin" "Kaido" ...
##  $ level       : chr [1:56] "Yonko" "Yonko" "Yonko" "Yonko" ...
##  $ affiliations: chr [1:56] "Red Haired Pirates" "Blackbeard Pirates" "Big Mom Pirates" "Beasts Pirates" ...
str(op_ages)
## tibble [482 × 2] (S3: tbl_df/tbl/data.frame)
##  $ name: chr [1:482] "Zunesha" "Jarul" "Jorul" "Hatcha" ...
##  $ age : num [1:482] 1000 408 344 188 160 160 160 159 156 153 ...
#or

glimpse(op_powers)
## Rows: 56
## Columns: 4
## $ power        <dbl> 100.0, 100.0, 100.0, 100.0, 99.0, 95.0, 95.0, 94.5, 94.0,…
## $ character    <chr> "Red Haired Shanks", "Marshall D. Teach", "Charlotte Linl…
## $ level        <chr> "Yonko", "Yonko", "Yonko", "Yonko", "Admiral", "Admiral",…
## $ affiliations <chr> "Red Haired Pirates", "Blackbeard Pirates", "Big Mom Pira…
glimpse(op_ages)
## Rows: 482
## Columns: 2
## $ name <chr> "Zunesha", "Jarul", "Jorul", "Hatcha", "Brogy", "Dorry", "Morley"…
## $ age  <dbl> 1000, 408, 344, 188, 160, 160, 160, 159, 156, 153, 141, 120, 105,…

2 Data Wrangling

2.1 Filtering

op_powers %>% 
  dplyr::filter(affiliations == "Marine")

2.2 Arranging

op_powers %>%
  arrange(character) #ascending, alphabetical order
  #arrange(desc(character)) #descending, alphabetical order

2.3 Recoding

law <- op_powers %>% 
  mutate(character02 = 
           recode(character, 
                  "Trafalgar D. Water Law" = "Trafalgar D. Law"))

law %>% filter(affiliations == "Heart Pirates") %>% 
  select(character, character02)

2.4 Slicing

op_powers %>% 
  slice(18L) #variable number 18
op_powers %>% 
  slice(n()) #the last variable
op_powers %>% 
  slice(50:n())
op_powers %>% 
  slice_min(character, n = 5, with_ties = FALSE)
op_powers %>% 
  slice_min(character, prop = 0.5, with_ties = TRUE)
op_powers %>% 
  slice_tail(n = 5)
op_powers %>% 
  slice_tail(prop = 0.5)
op_powers %>% 
  slice_max(affiliations, n = 5, with_ties = FALSE)
op_powers %>% 
  slice_max(affiliations, prop = 0.5, with_ties = TRUE)
op_powers %>% 
  slice_head(n = 5)
op_powers %>% 
  slice_head(prop = 0.5)

2.5 Selecting

db03 <- op_powers %>%
  select(character, affiliations)
db03
db04 <- op_powers %>% 
  select(-level)
db04

2.6 Relocating

db05 <- op_powers %>% 
  relocate(character, power, affiliations)
db05

2.7 Renaming

status <- op_powers %>% 
  rename("status" = "level")
status

2.8 Counting

op_powers %>% 
  filter(affiliations == "Marine") %>% 
  count() %>% 
  kableExtra::kbl() %>% 
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
n
10

2.9 Mutating

db06 <- op_powers %>% 
  mutate(anime = "One Piece",
         power_2 = power/2)

db06
db07 <- op_powers %>% 
  transmute(anime = "One Piece",
            power_2 = power/2)

db07

2.10 Grouping

db08 <- op_powers %>% 
  arrange(affiliations, desc(power)) %>% 
  group_by(affiliations) %>% 
  mutate(rank = row_number()) %>% 
  ungroup() %>% #close the group_by()
  arrange(affiliations) %>% 
  select(character, affiliations, rank)

db08

2.11 Summarising

db09 <- op_powers %>% 
  arrange(affiliations, desc(power)) %>% 
  group_by(affiliations) %>% 
  summarise(avg = mean(power, na.rm = TRUE),
            n = n()) %>%
  ungroup()

db09
db10a <- op_powers %>%
  mutate(fase1 = power*0.25,
         fase2 = power*0.75)

db10a
db10b <- db10a %>% 
  rowwise(character) %>%
  summarise(total = sum(fase1, fase2))
## `summarise()` has grouped output by 'character'. You can override using the `.groups` argument.
db10b

2.12 Dataset: Villain

villain_aff <- data.frame(
  character = c("Marshall D. Teach", "Charlotte Linlin", "Kaido", "Sakazuki Akainu", "Borsalino Kizaru"),
  affiliation = c("Blackbeard Pirates", "Big Mom Pirates", "Beasts Pirates", "Marine", "Marine")
)

character_power <- data.frame(
  name = c("Marshall D. Teach", "Kaido", "Sakazuki Akainu", "Monkey D. Dragon", "Silvers Rayleigh"),
  power = c(100, 100, 95, 99, 93)
)

2.13 Joining

#mutating joins
villain_aff %>% 
  left_join(character_power, by = c("character" = "name")) %>% 
  kableExtra::kbl() %>% 
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
character affiliation power
Marshall D. Teach Blackbeard Pirates 100
Charlotte Linlin Big Mom Pirates NA
Kaido Beasts Pirates 100
Sakazuki Akainu Marine 95
Borsalino Kizaru Marine NA 
#mutating joins
villain_aff %>% 
  right_join(character_power, by = c("character" = "name")) %>%
  kableExtra::kbl() %>% 
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
character affiliation power
Marshall D. Teach Blackbeard Pirates 100
Kaido Beasts Pirates 100
Sakazuki Akainu Marine 95
Monkey D. Dragon NA 99
Silvers Rayleigh NA 93 
#mutating joins
villain_aff %>% 
  inner_join(character_power, by = c("character" = "name"))  %>% 
  kableExtra::kbl() %>% 
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
character affiliation power
Marshall D. Teach Blackbeard Pirates 100
Kaido Beasts Pirates 100
Sakazuki Akainu Marine 95 
#mutating joins
villain_aff %>% 
  full_join(character_power, by = c("character" = "name"))  %>% 
  kableExtra::kbl() %>% 
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
character affiliation power
Marshall D. Teach Blackbeard Pirates 100
Charlotte Linlin Big Mom Pirates NA
Kaido Beasts Pirates 100
Sakazuki Akainu Marine 95
Borsalino Kizaru Marine NA
Monkey D. Dragon NA 99
Silvers Rayleigh NA 93 
#filtering joins
villain_aff %>% 
  semi_join(character_power, by = c("character" = "name")) %>% 
  kableExtra::kbl() %>% 
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
character affiliation
Marshall D. Teach Blackbeard Pirates
Kaido Beasts Pirates
Sakazuki Akainu Marine 
#filtering joins
villain_aff %>% 
  anti_join(character_power, by = c("character" = "name")) %>% 
  kableExtra::kbl() %>% 
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
character affiliation
Charlotte Linlin Big Mom Pirates
Borsalino Kizaru Marine

2.14 Conditional “ifelse”

(
  db11 <- op_powers %>%
    mutate(villain = ifelse(affiliations == "Blackbeard Pirates", "Villain",
                            "NA"))
)

2.15 Dataset: Luffy

luffy00 <- tribble(
  ~arc, ~power,
  "1-Punk Hazard", 75,
  "2-Dressrosa", NA,
  "3-Zou", 80,
  "4-Whole Cake Island", 82,
  "5-Levely", NA
)

kableExtra::kbl(luffy00) %>%
    kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power
1-Punk Hazard 75
2-Dressrosa NA
3-Zou 80
4-Whole Cake Island 82
5-Levely NA 
luffy00 <- luffy00 %>% 
  add_row(arc = "6- Wano Country",
          power = 85)

kableExtra::kbl(luffy00) %>%
    kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power
1-Punk Hazard 75
2-Dressrosa NA
3-Zou 80
4-Whole Cake Island 82
5-Levely NA
6- Wano Country 85 
is.na(luffy00)
##        arc power
## [1,] FALSE FALSE
## [2,] FALSE  TRUE
## [3,] FALSE FALSE
## [4,] FALSE FALSE
## [5,] FALSE  TRUE
## [6,] FALSE FALSE
#data frame
colSums(is.na(luffy00))
##   arc power 
##     0     2
mean(luffy00$power)
## [1] NA
mean(luffy00$power, na.rm = TRUE)
## [1] 80.5
#vector
which(is.na(luffy00))
## [1]  8 11
sum(is.na(luffy00)) 
## [1] 2

2.16 Treating “N/A”

luffy01 <- luffy00 %>%
  fill(power, .direction = "up") %>% 
  mutate(method = "fill")

kableExtra::kbl(luffy01) %>%
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power method
1-Punk Hazard 75 fill
2-Dressrosa 80 fill
3-Zou 80 fill
4-Whole Cake Island 82 fill
5-Levely 85 fill
6- Wano Country 85 fill 
luffy02 <- luffy00 %>%
  mutate(
    power = replace(power, is.na(power), mean(power, na.rm = TRUE)),
    method = "mean"
    )

#luffy02$power[is.na(luffy02$power)] <- mean(luffy02$power, na.rm = TRUE)
kableExtra::kbl(luffy02) %>%
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power method
1-Punk Hazard 75.0 mean
2-Dressrosa 80.5 mean
3-Zou 80.0 mean
4-Whole Cake Island 82.0 mean
5-Levely 80.5 mean
6- Wano Country 85.0 mean 
luffy03 <- luffy00 %>% 
  mutate(power = zoo::na.approx(power),
         method = "interpolate")

kableExtra::kbl(luffy03) %>%
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power method
1-Punk Hazard 75.0 interpolate
2-Dressrosa 77.5 interpolate
3-Zou 80.0 interpolate
4-Whole Cake Island 82.0 interpolate
5-Levely 83.5 interpolate
6- Wano Country 85.0 interpolate 
luffy00 %>% drop_na() %>% 
  kableExtra::kbl() %>% 
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power
1-Punk Hazard 75
3-Zou 80
4-Whole Cake Island 82
6- Wano Country 85

2.17 Binding

luffy04 <- rbind(luffy01, luffy02, luffy03)

luffy04 <- luffy01 %>%
  bind_rows(luffy02, luffy03)

kableExtra::kbl(luffy04) %>%
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power method
1-Punk Hazard 75.0 fill
2-Dressrosa 80.0 fill
3-Zou 80.0 fill
4-Whole Cake Island 82.0 fill
5-Levely 85.0 fill
6- Wano Country 85.0 fill
1-Punk Hazard 75.0 mean
2-Dressrosa 80.5 mean
3-Zou 80.0 mean
4-Whole Cake Island 82.0 mean
5-Levely 80.5 mean
6- Wano Country 85.0 mean
1-Punk Hazard 75.0 interpolate
2-Dressrosa 77.5 interpolate
3-Zou 80.0 interpolate
4-Whole Cake Island 82.0 interpolate
5-Levely 83.5 interpolate
6- Wano Country 85.0 interpolate 
luffy05 <- cbind(luffy01, luffy02, luffy03)

luffy05 <- luffy01 %>% 
  bind_cols(luffy02, luffy03)
## New names:
## * arc -> arc...1
## * power -> power...2
## * method -> method...3
## * arc -> arc...4
## * power -> power...5
## * ...
kableExtra::kbl(luffy05) %>%
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc…1 power…2 method…3 arc…4 power…5 method…6 arc…7 power…8 method…9
1-Punk Hazard 75 fill 1-Punk Hazard 75.0 mean 1-Punk Hazard 75.0 interpolate
2-Dressrosa 80 fill 2-Dressrosa 80.5 mean 2-Dressrosa 77.5 interpolate
3-Zou 80 fill 3-Zou 80.0 mean 3-Zou 80.0 interpolate
4-Whole Cake Island 82 fill 4-Whole Cake Island 82.0 mean 4-Whole Cake Island 82.0 interpolate
5-Levely 85 fill 5-Levely 80.5 mean 5-Levely 83.5 interpolate
6- Wano Country 85 fill 6- Wano Country 85.0 mean 6- Wano Country 85.0 interpolate

2.18 Long-table

# selecting variables
(
  db01a <-  op_powers %>%
    left_join(op_ages, by = c("character" = "name")) %>%
    select(-level) %>%
    relocate(character, affiliations, power, age)
)
# pivoting
(
  db01b <- db01a %>%
    pivot_longer(cols = power:age,
                 names_to = "variable",
                 values_to = "value")
)

2.19 Wide-table

(
  db01c <- db01b %>%
    pivot_wider(names_from = variable,
                values_from = value)
)

2.20 Exporting Table

writexl::write_xlsx(x = list(db01aSheet = db01a, db01bSheet = db01b, db01cSheet = db01c), path = "OnePiece.xlsx")

write.csv(db01a, file = "csv_db01a.csv")

2.21 Converting Characters

luffy06 <- luffy04 %>% 
    mutate_each(method, funs = toupper)
## Warning: `mutate_each_()` was deprecated in dplyr 0.7.0.
## Please use `across()` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated.
kableExtra::kbl(luffy06) %>%
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power method
1-Punk Hazard 75.0 FILL
2-Dressrosa 80.0 FILL
3-Zou 80.0 FILL
4-Whole Cake Island 82.0 FILL
5-Levely 85.0 FILL
6- Wano Country 85.0 FILL
1-Punk Hazard 75.0 MEAN
2-Dressrosa 80.5 MEAN
3-Zou 80.0 MEAN
4-Whole Cake Island 82.0 MEAN
5-Levely 80.5 MEAN
6- Wano Country 85.0 MEAN
1-Punk Hazard 75.0 INTERPOLATE
2-Dressrosa 77.5 INTERPOLATE
3-Zou 80.0 INTERPOLATE
4-Whole Cake Island 82.0 INTERPOLATE
5-Levely 83.5 INTERPOLATE
6- Wano Country 85.0 INTERPOLATE 
luffy07 <- luffy06 %>% 
    mutate_each(method, funs = tolower)

kableExtra::kbl(luffy07) %>%
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power method
1-Punk Hazard 75.0 fill
2-Dressrosa 80.0 fill
3-Zou 80.0 fill
4-Whole Cake Island 82.0 fill
5-Levely 85.0 fill
6- Wano Country 85.0 fill
1-Punk Hazard 75.0 mean
2-Dressrosa 80.5 mean
3-Zou 80.0 mean
4-Whole Cake Island 82.0 mean
5-Levely 80.5 mean
6- Wano Country 85.0 mean
1-Punk Hazard 75.0 interpolate
2-Dressrosa 77.5 interpolate
3-Zou 80.0 interpolate
4-Whole Cake Island 82.0 interpolate
5-Levely 83.5 interpolate
6- Wano Country 85.0 interpolate 
luffy08 <- luffy07 %>%
  mutate_if(is.character, str_to_upper)

kableExtra::kbl(luffy08) %>%
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power method
1-PUNK HAZARD 75.0 FILL
2-DRESSROSA 80.0 FILL
3-ZOU 80.0 FILL
4-WHOLE CAKE ISLAND 82.0 FILL
5-LEVELY 85.0 FILL
6- WANO COUNTRY 85.0 FILL
1-PUNK HAZARD 75.0 MEAN
2-DRESSROSA 80.5 MEAN
3-ZOU 80.0 MEAN
4-WHOLE CAKE ISLAND 82.0 MEAN
5-LEVELY 80.5 MEAN
6- WANO COUNTRY 85.0 MEAN
1-PUNK HAZARD 75.0 INTERPOLATE
2-DRESSROSA 77.5 INTERPOLATE
3-ZOU 80.0 INTERPOLATE
4-WHOLE CAKE ISLAND 82.0 INTERPOLATE
5-LEVELY 83.5 INTERPOLATE
6- WANO COUNTRY 85.0 INTERPOLATE 
luffy09 <- luffy08 %>%
  mutate_if(is.character, str_to_lower)

kableExtra::kbl(luffy09) %>%
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power method
1-punk hazard 75.0 fill
2-dressrosa 80.0 fill
3-zou 80.0 fill
4-whole cake island 82.0 fill
5-levely 85.0 fill
6- wano country 85.0 fill
1-punk hazard 75.0 mean
2-dressrosa 80.5 mean
3-zou 80.0 mean
4-whole cake island 82.0 mean
5-levely 80.5 mean
6- wano country 85.0 mean
1-punk hazard 75.0 interpolate
2-dressrosa 77.5 interpolate
3-zou 80.0 interpolate
4-whole cake island 82.0 interpolate
5-levely 83.5 interpolate
6- wano country 85.0 interpolate 
luffy10 <- luffy09 %>% 
    mutate_all(., .funs = toupper)

kableExtra::kbl(luffy10) %>%
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power method
1-PUNK HAZARD 75 FILL
2-DRESSROSA 80 FILL
3-ZOU 80 FILL
4-WHOLE CAKE ISLAND 82 FILL
5-LEVELY 85 FILL
6- WANO COUNTRY 85 FILL
1-PUNK HAZARD 75 MEAN
2-DRESSROSA 80.5 MEAN
3-ZOU 80 MEAN
4-WHOLE CAKE ISLAND 82 MEAN
5-LEVELY 80.5 MEAN
6- WANO COUNTRY 85 MEAN
1-PUNK HAZARD 75 INTERPOLATE
2-DRESSROSA 77.5 INTERPOLATE
3-ZOU 80 INTERPOLATE
4-WHOLE CAKE ISLAND 82 INTERPOLATE
5-LEVELY 83.5 INTERPOLATE
6- WANO COUNTRY 85 INTERPOLATE 
#drawback: converting numeric to character
luffy11 <- luffy09 %>%
  mutate(across(where(is.character), 
                  toupper))

kableExtra::kbl(luffy11) %>%
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power method
1-PUNK HAZARD 75.0 FILL
2-DRESSROSA 80.0 FILL
3-ZOU 80.0 FILL
4-WHOLE CAKE ISLAND 82.0 FILL
5-LEVELY 85.0 FILL
6- WANO COUNTRY 85.0 FILL
1-PUNK HAZARD 75.0 MEAN
2-DRESSROSA 80.5 MEAN
3-ZOU 80.0 MEAN
4-WHOLE CAKE ISLAND 82.0 MEAN
5-LEVELY 80.5 MEAN
6- WANO COUNTRY 85.0 MEAN
1-PUNK HAZARD 75.0 INTERPOLATE
2-DRESSROSA 77.5 INTERPOLATE
3-ZOU 80.0 INTERPOLATE
4-WHOLE CAKE ISLAND 82.0 INTERPOLATE
5-LEVELY 83.5 INTERPOLATE
6- WANO COUNTRY 85.0 INTERPOLATE 
luffy12 <- luffy11 %>% 
    mutate(across(where(is.character), 
                  tolower))

kableExtra::kbl(luffy12) %>%
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power method
1-punk hazard 75.0 fill
2-dressrosa 80.0 fill
3-zou 80.0 fill
4-whole cake island 82.0 fill
5-levely 85.0 fill
6- wano country 85.0 fill
1-punk hazard 75.0 mean
2-dressrosa 80.5 mean
3-zou 80.0 mean
4-whole cake island 82.0 mean
5-levely 80.5 mean
6- wano country 85.0 mean
1-punk hazard 75.0 interpolate
2-dressrosa 77.5 interpolate
3-zou 80.0 interpolate
4-whole cake island 82.0 interpolate
5-levely 83.5 interpolate
6- wano country 85.0 interpolate 
luffy13 <- luffy09 %>% 
    mutate(across(arc, tolower),
           across(method, toupper),
           across(power, round)
           )
kableExtra::kbl(luffy13) %>%
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power method
1-punk hazard 75 FILL
2-dressrosa 80 FILL
3-zou 80 FILL
4-whole cake island 82 FILL
5-levely 85 FILL
6- wano country 85 FILL
1-punk hazard 75 MEAN
2-dressrosa 80 MEAN
3-zou 80 MEAN
4-whole cake island 82 MEAN
5-levely 80 MEAN
6- wano country 85 MEAN
1-punk hazard 75 INTERPOLATE
2-dressrosa 78 INTERPOLATE
3-zou 80 INTERPOLATE
4-whole cake island 82 INTERPOLATE
5-levely 84 INTERPOLATE
6- wano country 85 INTERPOLATE

2.22 Substituting

luffy14 <- luffy13 %>% 
    mutate(
      power2 = gsub("[0-5]*", "", power), #taking out number 1 to 5
      arc2 = gsub(".*^", "0", arc), #adding 0 before the first number
      method2 = gsub("LL", "zz", method) #replacing LL to zz
      )

kableExtra::kbl(luffy14) %>%
  kableExtra::kable_styling(bootstrap_options = "striped", 
                full_width = F, 
                position = "left")
arc power method power2 arc2 method2
1-punk hazard 75 FILL 7 01-punk hazard FIzz
2-dressrosa 80 FILL 8 02-dressrosa FIzz
3-zou 80 FILL 8 03-zou FIzz
4-whole cake island 82 FILL 8 04-whole cake island FIzz
5-levely 85 FILL 8 05-levely FIzz
6- wano country 85 FILL 8 06- wano country FIzz
1-punk hazard 75 MEAN 7 01-punk hazard MEAN
2-dressrosa 80 MEAN 8 02-dressrosa MEAN
3-zou 80 MEAN 8 03-zou MEAN
4-whole cake island 82 MEAN 8 04-whole cake island MEAN
5-levely 80 MEAN 8 05-levely MEAN
6- wano country 85 MEAN 8 06- wano country MEAN
1-punk hazard 75 INTERPOLATE 7 01-punk hazard INTERPOLATE
2-dressrosa 78 INTERPOLATE 78 02-dressrosa INTERPOLATE
3-zou 80 INTERPOLATE 8 03-zou INTERPOLATE
4-whole cake island 82 INTERPOLATE 8 04-whole cake island INTERPOLATE
5-levely 84 INTERPOLATE 8 05-levely INTERPOLATE
6- wano country 85 INTERPOLATE 8 06- wano country INTERPOLATE

3 Data Visualisation

3.1 Datasets

op_ratings <- read_excel(path = "/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/KelasData/00_Datasets/OP_all.xlsx", sheet = "OP_ratings")

glimpse(op_ratings)
## Rows: 958
## Columns: 8
## $ rank           <dbl> 24129, 29290, 32043, 28818, 37113, 36209, 37648, 38371,…
## $ trend          <chr> "18", "11", "7", "8", "4", "4", "4", "6", "5", "4", "4"…
## $ season         <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1…
## $ episode        <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, …
## $ name           <chr> "I'm Luffy! The Man Who Will Become the Pirate King!", …
## $ start          <dbl> 1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 2000, 2…
## $ total_votes    <dbl> 647, 473, 428, 449, 370, 364, 344, 335, 327, 314, 310, …
## $ average_rating <dbl> 7.6, 7.8, 7.7, 8.1, 7.5, 7.7, 7.7, 7.7, 7.3, 7.5, 7.4, …
(
op_ratings02 <- op_ratings %>%
  select(episode, start, total_votes, average_rating) %>% 
  pivot_longer(cols = total_votes:average_rating,
               names_to = "variable",
               values_to = "value")
)

3.2 Palette: RColorBrewer

pacman::p_load(RColorBrewer)

#RColorBrewer
display.brewer.all(type = "qual")

display.brewer.all(type = "seq")

display.brewer.all(type = "div")

#display.brewer.pal(n = 12, name = "Set2")
#brewer.pal(n = 12, name = "Set3")
#display.brewer.pal(n = 11, name = "RdBu")

3.3 Palette: nord

pacman::p_load(nord)

nord_show_palette("snowstorm")

nord_show_palette("frost")

nord_show_palette("aurora")

nord_show_palette("lumina")

nord_show_palette("mountain_forms")

nord_show_palette("silver_mine")

nord_show_palette("lake_superior")

nord_show_palette("victory_bonds")

nord_show_palette("halifax_harbor")

nord_show_palette("moose_pond")

nord_show_palette("algoma_forest")

nord_show_palette("rocky_mountain")

nord_show_palette("red_mountain")

nord_show_palette("baie_mouton")

nord_show_palette("afternoon_prarie")

#hex-code: https://www.nordtheme.com/docs/colors-and-palettes

3.4 Palette: wesanderson

pacman::p_load(wesanderson)

#names(wes_palettes)
wes_palette("BottleRocket1")

wes_palette("BottleRocket2")

wes_palette("Rushmore1")

wes_palette("Royal1")

wes_palette("Royal2")

wes_palette("Zissou1")

wes_palette("Darjeeling1")

wes_palette("Darjeeling2")

wes_palette("Chevalier1")

wes_palette("FantasticFox1")

wes_palette("Moonrise1")

wes_palette("Moonrise2")

wes_palette("Moonrise3")

wes_palette("Cavalcanti1")

wes_palette("GrandBudapest1")

wes_palette("GrandBudapest2")

wes_palette("IsleofDogs1")

wes_palette("IsleofDogs2")

#hex-code: https://github.com/karthik/wesanderson/blob/master/R/colors.R
#scales::show_col(wes_palette("IsleofDogs2"))

3.5 Palette: viridis

pacman::p_load(viridis)

scales::show_col(viridis_pal(option = "viridis")(6))

scales::show_col(viridis_pal(option = "plasma")(6))

scales::show_col(viridis_pal(option = "rocket")(6))

scales::show_col(viridis_pal(option = "magma")(6))

scales::show_col(viridis_pal(option = "rocket")(6))

scales::show_col(viridis_pal(option = "mako")(6))

scales::show_col(viridis_pal(option = "inferno")(6))

3.6 Palette: Sequential

colorspace::hcl_palettes(type = "sequential", plot = TRUE)

3.7 Palette: Diverging

colorspace::hcl_palettes(type = "diverging", plot = TRUE, n = 9)

#colorspace::divergingx_palettes(plot = TRUE, n = 9)

3.8 Colorblind Friendly

(OkabeIto <- c("#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2",
             "#D55E00", "#CC79A7", "#000000"))
## [1] "#E69F00" "#56B4E9" "#009E73" "#F0E442" "#0072B2" "#D55E00" "#CC79A7"
## [8] "#000000"
#https://colorschemedesigner.com/csd-3.5/

pals::pal.bands(OkabeIto)

#Source: https://jfly.uni-koeln.de/color/#pallet
#Source: https://davidmathlogic.com/colorblind/#%23D81B60-%231E88E5-%23FFC107-%23004D40

3.9 Line chart: Base

(
line01 <- op_ratings02 %>% 
  ggplot(aes(x = episode, y = value)) +
  geom_line()
)

3.10 Line chart: Faceting

(
line02 <- op_ratings02 %>% 
  ggplot(aes(x = episode, y = value)) +
    geom_line() +
    facet_wrap(~variable, scales = "free", nrow = 2)
)

3.11 Line chart: Color and Theme

(
line02 <- op_ratings02 %>%
  #modify the dataset
  filter(start > 2015 & start < 2021) %>%
  mutate(variable = recode(variable,
                           average_rating = "Average Rating",
                           total_votes = "Total Votes"))  %>%
  #plot the dataset
  ggplot(aes(x = episode, y = value)) +
  facet_wrap(~variable, scales = "free", nrow = 2) +
  geom_line(color = "#0072B2") + #colorblind-friendly
  theme_test() #could be explored even further
)

3.12 Line chart: Coloring Based on Variable

(
line02 <- op_ratings02 %>%
  #modify the dataset
  filter(start > 2015 & start < 2021) %>%
  mutate(variable = recode(variable,
                           average_rating = "Average Rating",
                           total_votes = "Total Votes"))  %>%
  #plot the dataset
  ggplot(aes(x = episode, y = value)) +
  facet_wrap(~variable, scales = "free", nrow = 2) +
  geom_line(aes(color = start)) +
  theme_test() #could be explored even further
)

3.13 Line chart: Colorblind Palette

(
line02 <- op_ratings02 %>%
  #modify the dataset
  filter(start > 2015 & start < 2021) %>%
  mutate(variable = recode(variable,
                           average_rating = "Average Rating",
                           total_votes = "Total Votes"))  %>%
  #plot the dataset
  ggplot(aes(x = episode, y = value)) +
  facet_wrap(~variable, scales = "free", nrow = 2) +
  geom_line(aes(color = factor(start))) + 
  ggthemes::scale_color_colorblind() +
  theme_test() #could be explored even further
)

3.14 Line Chart: Coloring Manual

(
line02 <- op_ratings02 %>%
  #modify the dataset
  filter(start > 2015 & start < 2021) %>%
  mutate(variable = recode(variable,
                           average_rating = "Average Rating",
                           total_votes = "Total Votes"))  %>%
  #plot the dataset
  ggplot(aes(x = episode, y = value)) +
  facet_wrap(~variable, scales = "free", nrow = 2) +
  geom_line(aes(color = factor(variable))) + 
  scale_color_manual(values = c("blue", "red")) +
  theme_test() #could be explored even further
)

3.15 Line chart: Modification

(
  line03 <- op_ratings02 %>%
    filter(start > 2015 & start < 2021) %>%
    mutate(
      variable = recode(variable,
                        average_rating = "Average Rating",
                        total_votes = "Total Votes")
    )  %>%
    ggplot(aes(x = episode, y = value)) +
    geom_line(aes(color = factor(start))) +
    #scale_color_brewer(palette = "Set1") +
    nord::scale_color_nord("aurora", discrete = TRUE) +
    facet_wrap(
      ~ variable,
      scales = "free",
      nrow = 2,
      strip.position = "right"
    ) +
    theme_test() +
    theme(
      legend.position = "bottom",
      plot.title = element_text(hjust = 0, size = 16, face = "bold"),
      plot.subtitle = element_text(hjust = 0, size = 14),
      plot.caption = element_text(hjust = 0, size = 8),
      plot.title.position = "plot",
      plot.caption.position = "plot"
    ) +
    labs(
      title = "One Piece",
      subtitle = "Ratings and Votes",
      caption = "\nSource: https://www.kaggle.com/aditya2803",
      x = "Episode",
      y = ""
    ) +
    guides(
      color = guide_legend(title = "Year release:"),
      fill = guide_legend(title = "Year release:")
    )
)

3.16 Line chart: Adding points

(
line03 <- op_ratings02 %>% 
  filter(start > 2015 & start < 2021) %>%
  mutate(variable = recode(variable, average_rating = "Average Rating",
                           total_votes = "Total Votes")
         ) %>% 
  ggplot(aes(x = episode, y = value)) +
  facet_wrap(vars(variable), nrow = 2, scales = "free",
             as.table = TRUE, strip.position = "right") +
  geom_line(aes(color = factor(start))) +
  scale_color_brewer(palette = "Set1") +
  theme_classic() +
  #ggthemes::theme_economist() +
  theme(legend.position = "bottom",
        plot.title = element_text(hjust = 0, size = 16,
                              face = "bold"),
    plot.subtitle = element_text(hjust = 0, size = 13),
    plot.caption = element_text(hjust = 0, size = 8),
    plot.title.position = "plot",
    plot.caption.position =  "plot",) +
  labs(title = "One Piece",
       subtitle = "Ratings and Votes",
       y = "",
       x = "Episode",
       caption = "\nSource: https://www.kaggle.com/aditya2803") +
  geom_point(aes(color = factor(start), fill = factor(start)), 
             shape = 21, size = 1, alpha = 0.5) +
  scale_fill_brewer(palette = "Set1") +
  guides(color = guide_legend(title = "Year release:"),
         fill = guide_legend(title = "Year release:"))
)

3.17 Point chart: Dataset

(
db02 <- db01c %>% 
  arrange(desc(power)) %>% 
  slice_max(power, n = 15, with_ties = TRUE)
)

3.18 Point chart: Base

(
  point01 <- ggplot(db02, mapping = aes(x = character, y = age))
)

## Point chart: Flipping

(
  point01 + coord_flip()
)

## Point chart: Assigning the function

point01 + 
  coord_flip() +
  geom_point()

## Point chart: Defining the color

(
  point01 + 
  coord_flip() +
  geom_point(color = "blue",
             shape = 0,
             size = 5)
)

3.19 Point chart: Changing the shape

(
  point01 + 
  coord_flip() +
  geom_point(color = "blue",
             shape = 21,
             size = 3)
)

## Point chart: Size

(
  point02 <- db02 %>% 
    ggplot(aes(character, age, size = power)) +
    coord_flip() +
    geom_point()
)

3.20 Point chart: Reorder

(
  point03 <- db02 %>% 
    ggplot(aes(reorder(character, power), age, size = power)) +
    coord_flip() +
    geom_point()
)

3.21 Static Plot: No Faceting

(point04 <- op_powers %>%
  left_join(op_ages, by = c("character" = "name")) %>%
  relocate(character, age, power) %>%
  #group_by(level) %>%
  slice_max(power, n = 15, with_ties = FALSE) %>%
  #ungroup() %>%
  ggplot(aes(x = reorder(character, power),
             y = age)) +
  geom_point(aes(color = factor(affiliations), size = power)) +
  #coord_cartesian(expand = TRUE, clip = "on") +
  coord_flip() +
  nord::scale_color_nord("aurora") +
  xlab("") +
  ylab("Age") +
  theme_test() +
  theme(
    axis.text.x = element_text(size = 8),
    axis.ticks.x = element_blank(),
    axis.line.x = element_blank(),
    axis.title.x = element_text(size = 7),
    axis.line.y = element_blank(),
    axis.title.y = element_text(size = 7),
    axis.text.y = element_text(size = 8),
    plot.title.position = "plot",
    plot.caption.position = "plot",
    legend.title = element_text(size = 7),
    legend.text = element_text(size = 7),
    legend.key.size = unit(0.5, "cm"),
    legend.spacing = unit(1, "cm"),
    plot.title = element_text(hjust = 0, size = 13, face = "bold"),
    plot.subtitle = element_text(hjust = 0, size = 12),
    plot.caption = element_text(hjust = 0, size = 12),
    # legend.title = element_blank(),
    legend.position = "right",
    strip.text.x = element_text(size = 8),
    panel.grid.major.y = element_line(colour = "grey97"),
    panel.ontop = FALSE,
    panel.spacing = unit(1, "lines")
  ) +
  guides(size = guide_legend("Power"), color = guide_legend("Affiliation")) +
  labs(title = "The top 15-most powerful characters",
       subtitle = "",
       caption = "") +
  scale_size_continuous(range = c(1, 5)) +
  scale_y_continuous(limits = c(10, 90),
                     breaks = c(20, 50, 80))
)

3.22 Static Plot: With Faceting

(point05 <- op_powers %>%
  left_join(op_ages, by = c("character" = "name")) %>%
  relocate(character, age, power) %>%
  #group_by(level) %>%
  slice_max(power, n = 15, with_ties = FALSE) %>%
  #ungroup() %>%
  ggplot(aes(x = reorder(character, power),
             y = age)) +
  geom_point(aes(color = factor(affiliations), size = power)) +
  coord_cartesian(expand = TRUE, clip = "on") +
  coord_flip() +
  nord::scale_color_nord("aurora") +
  xlab("") +
  ylab("Age") +
  theme_test() +
  theme(
    axis.text.x = element_text(size = 8),
    axis.ticks.x = element_blank(),
    axis.line.x = element_blank(),
    axis.title.x = element_text(size = 7),
    axis.line.y = element_blank(),
    axis.title.y = element_text(size = 7),
    axis.text.y = element_text(size = 8),
    plot.title.position = "plot",
    plot.caption.position = "plot",
    legend.title = element_text(size = 7),
    legend.text = element_text(size = 7),
    legend.key.size = unit(0.5, "cm"),
    legend.spacing = unit(1, "cm"),
    plot.title = element_text(hjust = 0, size = 13, face = "bold"),
    plot.subtitle = element_text(hjust = 0, size = 12),
    plot.caption = element_text(hjust = 0, size = 12),
    # legend.title = element_blank(),
    legend.position = "right",
    strip.text.x = element_text(size = 8),
    panel.grid.major.y = element_line(colour = "grey97"),
    panel.ontop = FALSE,
    panel.spacing = unit(1, "lines")
  ) +
  guides(size = guide_legend("Power"), color = guide_legend("Affiliation")) +
  labs(title = "The top 15-most powerful characters",
       subtitle = "",
       caption = "") +
  scale_size_continuous(range = c(1, 5)) +
  scale_y_continuous(limits = c(10, 90),
                     breaks = c(20, 50, 80)) +
  facet_grid(. ~ level)
)
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.

3.23 Saving Image

ggsave(
  filename = "point05.png",
  #filename = "point05.pdf",
  plot = point05,
  #device = cairo_pdf,
  width = 297,
  height = 210,
  units = "mm"
)

3.24 Interactive Plot: No Faceting

point06 <- op_powers %>%
  left_join(op_ages, by = c("character" = "name")) %>%
  relocate(character, age, power) %>%
  #group_by(level) %>%
  slice_max(power, n = 15, with_ties = FALSE) %>%
  #ungroup() %>%
  mutate(text = paste(
    "Character: ", reorder(character, power), 
    "\nAffiliation: ", factor(affiliations), 
    "\nAge: ", age, 
    "\nPower: ", power, 
    sep = "")) %>%
  ggplot(aes(x = reorder(character, power),
             y = factor(affiliations),
             text = text)) +
  geom_point(aes(color = age, size = power)) +
  coord_cartesian(expand = TRUE, clip = "on") +
  coord_flip() +
  #nord::scale_color_nord("victory_bonds", discrete = FALSE) +
  viridis::scale_colour_viridis(option = "viridis", direction = -1) +
  xlab("") +
  ylab("") +
  theme_test() +
  theme(
    axis.text.x = element_text(
      size = 8,
      angle = 90,
      vjust = 0.5,
      hjust = 1
    ),
    axis.ticks.x = element_blank(),
    axis.line.x = element_blank(),
    axis.title.x = element_text(size = 7),
    axis.line.y = element_blank(),
    axis.title.y = element_text(size = 7),
    axis.text.y = element_text(size = 8),
    plot.title.position = "plot",
    plot.caption.position = "plot",
    legend.title = element_text(size = 7),
    legend.text = element_text(size = 7),
    legend.key.size = unit(0.5, "cm"),
    legend.spacing = unit(1, "cm"),
    plot.title = element_text(hjust = 0, size = 13, face = "bold"),
    plot.subtitle = element_text(hjust = 0, size = 12),
    plot.caption = element_text(hjust = 0, size = 12),
    # legend.title = element_blank(),
    legend.position = "none",
    strip.text.x = element_text(size = 8),
    panel.grid.major.y = element_line(colour = "grey97"),
    panel.ontop = FALSE
  ) +
  guides(size = guide_legend("Power"), color = guide_colorbar("Age")) +
  labs(title = "",
       subtitle = "",
       caption = "") +
  scale_size_continuous(range = c(1, 5))
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
ggplotly(point06, tooltip = "text")

Figure 3: The top 15-most powerful characters, without facet_grid(. ~ level)

3.25 Interactive Plot: With Faceting

point07 <- op_powers %>% 
  left_join(op_ages, by = c("character" = "name")) %>% 
  relocate(character, age, power) %>% 
  #group_by(level) %>% 
  slice_max(power, n = 15, with_ties = FALSE) %>%
  #ungroup() %>% 
  mutate(text = paste(
    "Character: ", reorder(character, power), 
    "\nAffiliation: ", factor(affiliations), 
    "\nAge: ", age, 
    "\nPower: ", power, 
    sep = "")) %>%
  ggplot(aes(x = reorder(character, power), 
             y = factor(affiliations),
             text = text)) +
  geom_point(aes(color = age, size = power)) +
  coord_cartesian(expand = TRUE, clip = "on") +
  coord_flip() +
  #nord::scale_color_nord("victory_bonds", discrete = FALSE) +
  viridis::scale_colour_viridis(option = "viridis", direction = -1) +
  xlab("") +
  ylab("") +
  theme_test() +
  theme(
    axis.text.x = element_text(size = 8, angle = 90, vjust = 0.5, hjust=1),
    axis.ticks.x = element_blank(),
    axis.line.x = element_blank(),
    axis.title.x = element_text(size = 7),
    axis.line.y = element_blank(),
    axis.title.y = element_text(size = 7),
    axis.text.y = element_text(size = 8),
    plot.title.position = "plot",
    plot.caption.position = "plot",
    legend.title = element_text(size = 7),
    legend.text = element_text(size = 7),
    legend.key.size = unit(0.5, "cm"),
    legend.spacing = unit(1, "cm"),
    plot.title = element_text(
      hjust = 0, size = 13, face = "bold"
    ),
    plot.subtitle = element_text(hjust = 0, size = 12),
    plot.caption = element_text(hjust = 0, size = 12),
    # legend.title = element_blank(),
    legend.position = "none",
    strip.text.x = element_text(size = 8),
    panel.grid.major.y = element_line(colour = "grey97"),
    panel.ontop = FALSE,
    panel.spacing = unit(1, "lines")
  ) +
  guides(size = guide_legend("Power"), color = guide_colorbar("Age")) +
  labs(
    title = "",
    subtitle = "",
    caption = ""
  ) +
  scale_size_continuous(range = c(1,5)) +
  facet_grid(.~level)
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
ggplotly(point07, tooltip = "text")

Figure 4: The top 15-most powerful characters, with facet_grid(. ~ level)

4 Clearing

#clearing the environment
ls()
##  [1] "character_power" "db01a"           "db01b"           "db01c"          
##  [5] "db02"            "db03"            "db04"            "db05"           
##  [9] "db06"            "db07"            "db08"            "db09"           
## [13] "db10a"           "db10b"           "db11"            "law"            
## [17] "line01"          "line02"          "line03"          "luffy00"        
## [21] "luffy01"         "luffy02"         "luffy03"         "luffy04"        
## [25] "luffy05"         "luffy06"         "luffy07"         "luffy08"        
## [29] "luffy09"         "luffy10"         "luffy11"         "luffy12"        
## [33] "luffy13"         "luffy14"         "OkabeIto"        "op_ages"        
## [37] "op_powers"       "op_ratings"      "op_ratings02"    "point01"        
## [41] "point02"         "point03"         "point04"         "point05"        
## [45] "point06"         "point07"         "status"          "villain_aff"
rm(list=ls())

5 Acknowledgements

5.1 References

5.2 Datasets

 

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