---
title: "MyAnimeList Data"
output:
flexdashboard::flex_dashboard:
source_code: embed
vertical_layout: scroll
theme: yeti
---
```{r, echo = F, warning = F, message = F}
# packages
library(tidyverse)
library(plotly)
library(highcharter)
library(flexdashboard)
library(crosstalk)
library(DT)
library(data.table)
# highcharter default theme change
options(highcharter.theme = hc_theme_538())
```
```{r}
# data importation
data = read.csv(file = "./data/anime_filtered.csv",
sep = ",",
stringsAsFactors = F)
```
```{r}
# dropping unused columns
data = data %>%
select(-title_synonyms, -status, -airing, -aired_string, -background, -premiered,
-broadcast, -related, -producer, -licensor, -opening_theme, -ending_theme)
# MyAnimeList changed his website structure, adapting the image URL
data = data %>%
mutate(image_url = str_replace(image_url, "myanimelist.cdn-dena.com", "cdn.myanimelist.net"))
# Some animes have wrong image path (detected while working on data, this list isn't complete)
data$image_url[data$title == "Steins;Gate 0"] = "https://cdn.myanimelist.net/images/anime/1375/93521.jpg"
data$type = as.factor(data$type)
data$rating = as.factor(data$rating)
```
```{r}
# Extracting start date, year, month, season, decade from aired
# Anime seasons follow TV seasons and are 3 months long in Japan
data = data %>%
rowwise() %>%
mutate(aired = str_extract_all(aired, "(None|[0-9]*-[0-9]+-[0-9]+)")[[1]][1]) %>%
ungroup()
data = data %>%
mutate(year = as.integer(if_else(nchar(aired) == 10, substr(aired, 1, 4), NULL)),
month = as.integer(if_else(nchar(aired) == 10, substr(aired, 6, 7), NULL)),
season = if_else(month %in% c(1:3), "Winter",
if_else(month %in% c(4:6), "Spring",
if_else(month %in% c(7:9), "Summer",
if_else(month %in% c(10:12), "Autumn", NULL)))),
year_season = paste(year, season),
decade = as.factor(if_else(!is.na(year),
paste(substr(year, 1, 3), "0's", sep = ""),
NULL))) %>%
arrange(year, month)
# Extracting duration in minutes and creating duration classes
data = data %>% mutate(hours = if_else(str_detect(duration, "[0-9]*(?= hr.)"),
as.numeric(str_extract(duration, "[0-9]*(?= hr.)")),
0),
minutes = if_else(str_detect(duration, "[0-9]*(?= min.)"),
as.numeric(str_extract(duration, "[0-9]*(?= min.)")),
0),
seconds = if_else(str_detect(duration, "[0-9]*(?= sec.)"),
as.numeric(str_extract(duration, "[0-9]*(?= sec.)")),
0),
duration = hours*60 + minutes + seconds/60,
duration = na_if(duration, 0)) %>%
select(-hours, -minutes, -seconds)
data$duration_class = cut(data$duration, c(0, 5, 15, 30, 45, 60, 120, Inf),
labels = c("Less than 5 minutes", "Between 6 and 15 minutes", "Between 16 and 30 minutes",
"Between 31 and 45 minutes", "Between 46 and 60 minutes", "Between 1 and 2 hours", "More than 2 hours"),
include.lowest = T)
data$duration_class = factor(data$duration_class, levels = c(levels(data$duration_class), "Unknown"))
data$duration_class[is.na(data$duration_class)] = "Unknown"
```
```{r, echo = F}
# Unavailable genres are coded as "Unknown"
data[data$genre == "", "genre"] = "Unknown"
# Extracting list of unique genres
a = data$genre
tot_genres = unlist(str_split(a, ", "))
liste_genres = unique(tot_genres)
```
```{js}
$('.navbar-inverse').removeClass('navbar-inverse').addClass('navbar-default');
```
Presentation {data-icon="fa-home"}
===========================================================
### presentation txt {.no-title}
Presentation
This is a dashboard about animes (TV, Movies, and others). You can find out details about anime types, genres, evolution, scores, etc. If the first tab gives a first insight of anime world, the two next ones focus on the two main anime types : TV and Movies. The last tab allows you to examine the different anime studios separately.
Check out the "about" tab to know the data sources, inspirations, acknowledgements and tools used here.
The dashboard is fully interactive, do not hesitate to put your mouse on visualisations and try to click on Anime photos to be redirected to the MyAnimeList's anime page!
**Please enjoy your visit here, and don't hesitate to ask questions in comments!**
{height=320px}
Overview {data-orientation=columns data-icon="fa-eye"}
===========================================================
Column {.colored}
-----------------------------------------------------------
### Anime types {.no-title}
```{r fig.height=2.5}
data_pie_type = data %>%
filter(type != "Unknown") %>%
group_by("Type" = type) %>%
summarise(Freq = n())
highchart() %>%
hc_add_series(data_pie_type,
hcaes(x = Type,
y = Freq,
color = Type),
type = "pie") %>%
hc_tooltip(borderWidth = 1.5,
headerFormat = "",
pointFormat = paste("Type: {point.Type} ({point.percentage:.1f}%)
Count: {point.y}")) %>%
hc_title(text = "Anime types repartition")
```
### Duration x Type {.no-title}
```{r fig.height=3}
data_col_type_duration_class = data %>%
filter(type != "Unknown", duration_class != "Unknown") %>%
group_by(type, duration_class) %>%
summarise(Freq = n())
highchart() %>%
hc_add_series(data_col_type_duration_class,
hcaes(x = type,
y = Freq,
group = duration_class),
type = "column") %>%
hc_title(text = "Anime duration per type") %>%
hc_xAxis(categories = levels(data_col_type_duration_class$type),
labels = list(style = list(fontSize = 8))) %>%
hc_yAxis(title = list(text = "Count")) %>%
hc_tooltip(useHTML = T,
borderWidth = 1.5,
headerFormat = "",
pointFormat = paste("{point.type}
{point.duration_class}
{point.y}")) %>%
hc_legend(enabled = F)
```
### evolution {.no-title}
```{r fig.height=2.5}
data_line_year = data %>%
filter(!is.na(year)) %>%
group_by("Year" = year) %>%
summarise(Freq = n())
highchart() %>%
hc_add_series(data_line_year,
hcaes(x = Year,
y = Freq,
color = Freq),
type = "line") %>%
hc_title(text = "Number of animes per year") %>%
hc_xAxis(title = list(text = "Year")) %>%
hc_yAxis(title = list(text = "Count")) %>%
hc_tooltip(useHTML = T,
borderWidth = 1.5,
headerFormat = "",
pointFormat = paste("{point.Year}
{point.Freq} animes")) %>%
hc_legend(enabled = F)
```
Column {.colored}
-----------------------------------------------------------
### animes (TV, movies, ONA, OVA, etc.) from 1917 to 2018
```{r fig.height=0.4}
nb_anime <- format(nrow(data), big.mark = ",")
valueBox(nb_anime, icon = "fa-play", color = '#968fff')
```
### Genres repartition {.no-title}
```{r}
data_bar_genres = table("Genre" = tot_genres) %>%
as.data.frame() %>%
arrange(-Freq)
highchart() %>%
hc_add_series(data_bar_genres,
hcaes(x = Genre,
y = Freq,
color = Freq),
type = "bar") %>%
hc_title(text = "Anime genres") %>%
hc_xAxis(categories = data_bar_genres$Genre,
labels = list(style = list(fontSize = 12)),
min = 0,
max = 15,
scrollbar = list(enabled = T)) %>%
hc_yAxis(title = list(text = "Count"),
min = 0,
max = 5500) %>%
hc_tooltip(useHTML = T,
borderWidth = 1.5,
headerFormat = "",
pointFormat = paste("{point.Genre}
{point.Freq} animes")) %>%
hc_plotOptions(bar = list(stacking = "normal",
pointPadding = 0,
groupPadding = 0,
borderWidth = 2,
borderColor = "#DBDBDB")) %>%
hc_legend(enabled = FALSE)
```
### Most popular anime {.no-title .bgcolored}
```{r}
data_most_popular = data %>%
filter(popularity == 1) %>%
select(anime_id, title, image_url, score, members) %>%
mutate(url_mal = paste("https://myanimelist.net/anime/", anime_id, sep = ""))
data_most_liked = data %>%
filter(rank == 1) %>%
select(anime_id, title, image_url, score, members) %>%
mutate(url_mal = paste("https://myanimelist.net/anime/", anime_id, sep = ""))
```
| Most popular anime |
Most liked anime |
| `r data_most_popular$title` |
`r data_most_liked$title` |
|
[{height=320px .imgw}](`r data_most_popular$url_mal`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=320px .imgw}](`r data_most_liked$url_mal`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."} |
| `r format(data_most_popular$members, big.mark = ",")` members |
`r format(data_most_liked$members, big.mark = ",")` members |
| `r data_most_popular$score`/10 |
`r data_most_liked$score`/10 |
TV Anime {data-orientation=rows data-icon="fa-tv"}
===========================================================
```{r}
data_anime_tv = data %>%
filter(type == "TV")
```
Row
-----------------------------------------------------------
```{r}
data_most_episodes = data_anime_tv %>%
arrange(-episodes) %>%
slice(1)
nb_anime_tv = nrow(data_anime_tv)
time_anime_watch = round(sum(data_anime_tv$episodes * data_anime_tv$duration, na.rm = T)/60/24/30.33/12, 0)
```
### from 1917 to 2018
```{r}
valueBox(paste(format(nb_anime_tv, big.mark = ","), "TV animes"),
icon = "fa-database", color = '#ffdc8f')
```
### `r data_most_episodes$title` is the #1 Anime with the most episodes
```{r}
valueBox(paste(format(data_most_episodes$episodes, big.mark = ","), "episodes"),
icon = "fa-list", color = '#8fa7ff')
```
### to watch every episode of every TV anime
```{r}
valueBox(paste(time_anime_watch, "years"),
icon = "fa-clock", color = '#8fff93')
```
Row
-----------------------------------------------------------
### Avg score per year {.no-title}
```{r, fig.width= 5}
data_line_score_avg = data_anime_tv %>%
filter(score != 0, scored_by > 10) %>%
group_by("Year" = year) %>%
summarise(avg = round(mean(score, na.rm = T), 2))
highchart() %>%
hc_add_series(data_line_score_avg,
hcaes(x = Year,
y = avg,
color = avg),
type = "line") %>%
hc_title(text = "Average score per year") %>%
hc_xAxis(title = list(text = "Year")) %>%
hc_yAxis(title = list(text = "Average score")) %>%
hc_tooltip(useHTML = T,
borderWidth = 1.5,
headerFormat = "",
pointFormat = paste("{point.Year}
{point.avg}/10")) %>%
hc_legend(enabled = F)
```
### rating {.no-title}
```{r, fig.width= 5}
data_bar_rating = data_anime_tv %>%
filter(!is.na(decade)) %>%
group_by("Decade" = decade, rating,
.drop = F) %>%
summarise(Freq = n())
highchart() %>%
hc_add_series(data_bar_rating,
hcaes(x = Decade,
y = Freq,
group = rating),
type = "line") %>%
hc_title(text = "Ratings evolution during decades") %>%
hc_xAxis(title = list(text = "Decade"),
categories = unique(data_bar_rating$Decade)) %>%
hc_yAxis(title = list(text = "Count")) %>%
hc_tooltip(useHTML = T,
borderWidth = 1.5,
headerFormat = "",
pointFormat = paste("
{point.rating}
{point.Decade}
{point.Freq}"))
```
### duration {.no-title}
```{r, fig.width= 5}
data_bar_duration = data_anime_tv %>%
filter(!is.na(duration)) %>%
mutate(duration = ceiling(duration)) %>%
group_by(duration) %>%
summarise(Freq = n())
highchart() %>%
hc_add_series(data_bar_duration,
hcaes(x = duration,
y = Freq,
color = duration),
type = "column") %>%
hc_title(text = "Anime duration repartition") %>%
hc_xAxis(title = list(text = "Duration (minutes)")) %>%
hc_yAxis(title = list(text = "Count")) %>%
hc_tooltip(useHTML = T,
borderWidth = 1.5,
headerFormat = "",
pointFormat = paste("{point.duration} minutes
{point.Freq} TV animes")) %>%
hc_legend(enabled = F)
```
Row
-----------------------------------------------------------
### Episodes {.no-title}
```{r, fig.width= 5, fig.height= 1}
data_bar_episodes = data_anime_tv %>%
filter(!is.na(episodes), episodes < 110) %>%
group_by(episodes) %>%
summarise(Freq = n())
n_omit_episodes = data_anime_tv %>%
filter(!is.na(episodes), episodes >= 110) %>%
nrow()
highchart() %>%
hc_add_series(data_bar_episodes,
hcaes(x = episodes,
y = Freq,
color = episodes),
type = "column") %>%
hc_title(text = "Anime episodes repartition") %>%
hc_subtitle(text = paste(n_omit_episodes, "animes have more than 110 episodes and have been removed")) %>%
hc_xAxis(title = list(text = "Episodes")) %>%
hc_yAxis(title = list(text = "Count")) %>%
hc_tooltip(useHTML = T,
borderWidth = 1.5,
headerFormat = "",
pointFormat = paste("{point.episodes} minutes
{point.Freq} TV animes")) %>%
hc_legend(enabled = F)
```
### density {.no-title}
```{r}
data_anime_clean = data_anime_tv %>%
filter(!is.na(decade), score != 0)
densities = map(unique(data_anime_clean$decade), function(x){
dt <- density(data_anime_clean$score[data_anime_clean$decade == x])[1:2]
dt <- list_parse2(as.data.frame(dt))
list(data = dt, name = x)
})
highchart() %>%
hc_add_series_list(densities) %>%
hc_title(text = "Score density per decade") %>%
hc_xAxis(title = list(text = "Score"),
min = 0,
max = 10) %>%
hc_yAxis(title = list(text = "Density")) %>%
hc_tooltip(useHTML = T,
borderWidth = 1.5,
headerFormat = "",
pointFormat = paste("{point.series.name}"))
```
Row
-----------------------------------------------------------
### Most popular TV animes {.no-title .bgcolored}
```{r}
data_anime_tv_most_popular = data_anime_tv %>%
filter(popularity != 0) %>%
arrange(popularity) %>%
slice(1:5) %>%
select(anime_id, title, image_url, score, members) %>%
mutate(url_mal = paste("https://myanimelist.net/anime/", anime_id, sep = ""))
```
Most popular animes
| `r data_anime_tv_most_popular$title[1]` |
`r data_anime_tv_most_popular$title[2]` |
`r data_anime_tv_most_popular$title[3]` |
`r data_anime_tv_most_popular$title[4]` |
`r data_anime_tv_most_popular$title[5]` |
| [{height=200px .imgw}](`r data_anime_tv_most_popular$url_mal[1]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_tv_most_popular$url_mal[2]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_tv_most_popular$url_mal[3]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_tv_most_popular$url_mal[4]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_tv_most_popular$url_mal[5]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
| #1 |
#2 |
#3 |
#4 |
#5 |
| `r format(data_anime_tv_most_popular$members[1], big.mark = ",")` members |
`r format(data_anime_tv_most_popular$members[2], big.mark = ",")` members |
`r format(data_anime_tv_most_popular$members[3], big.mark = ",")` members |
`r format(data_anime_tv_most_popular$members[4], big.mark = ",")` members |
`r format(data_anime_tv_most_popular$members[5], big.mark = ",")` members |
| `r data_anime_tv_most_popular$score[1]`/10 {height=12px} |
`r data_anime_tv_most_popular$score[2]`/10 {height=12px} |
`r data_anime_tv_most_popular$score[3]`/10 {height=12px} |
`r data_anime_tv_most_popular$score[4]`/10 {height=12px} |
`r data_anime_tv_most_popular$score[5]`/10 {height=12px} |
Row
-----------------------------------------------------------
### Most liked TV animes {.no-title .bgcolored}
```{r}
data_anime_tv_most_liked = data_anime_tv %>%
filter(rank != 0) %>%
arrange(rank) %>%
slice(1:5) %>%
select(anime_id, title, image_url, score, members) %>%
mutate(url_mal = paste("https://myanimelist.net/anime/", anime_id, sep = ""))
```
Most liked animes
| `r data_anime_tv_most_liked$title[1]` |
`r data_anime_tv_most_liked$title[2]` |
`r data_anime_tv_most_liked$title[3]` |
`r data_anime_tv_most_liked$title[4]` |
`r data_anime_tv_most_liked$title[5]` |
| [{height=200px .imgw}](`r data_anime_tv_most_liked$url_mal[1]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_tv_most_liked$url_mal[2]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_tv_most_liked$url_mal[3]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_tv_most_liked$url_mal[4]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_tv_most_liked$url_mal[5]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
| #1 |
#2 |
#3 |
#4 |
#5 |
| `r format(data_anime_tv_most_liked$members[1], big.mark = ",")` members |
`r format(data_anime_tv_most_liked$members[2], big.mark = ",")` members |
`r format(data_anime_tv_most_liked$members[3], big.mark = ",")` members |
`r format(data_anime_tv_most_liked$members[4], big.mark = ",")` members |
`r format(data_anime_tv_most_liked$members[5], big.mark = ",")` members |
| `r data_anime_tv_most_liked$score[1]`/10 {height=12px} |
`r data_anime_tv_most_liked$score[2]`/10 {height=12px} |
`r data_anime_tv_most_liked$score[3]`/10 {height=12px} |
`r data_anime_tv_most_liked$score[4]`/10 {height=12px} |
`r data_anime_tv_most_liked$score[5]`/10 {height=12px} |
Movie {data-orientation=rows data-icon="fa-film"}
===========================================================
```{r}
data_anime_mv = data %>%
filter(type == "Movie")
```
Row
-----------------------------------------------------------
```{r}
data_anime_mv_longest = data_anime_mv %>%
arrange(-duration) %>%
slice(1)
nb_anime_mv = nrow(data_anime_mv)
time_mv_watch = round(sum(data_anime_mv$episodes * data_anime_mv$duration, na.rm = T)/60/24/30.33, 0)
```
### from 1917 to 2018
```{r}
valueBox(paste(format(nb_anime_mv, big.mark = ","), "Movies"),
icon = "fa-database", color = '#ffdc8f')
```
### `r data_anime_mv_longest$title` is the #1 longest Anime Movie
```{r}
valueBox(paste(format(data_anime_mv_longest$duration, big.mark = ","), "minutes"),
icon = "fa-clock", color = '#d28fff')
```
### to watch every episode of every Anime Movie
```{r}
valueBox(paste(time_mv_watch, "months"),
icon = "fa-clock", color = '#8fff93')
```
Row
-----------------------------------------------------------
### Avg score per year MV {.no-title}
```{r, fig.width= 5}
data_line_score_avg_mv = data_anime_mv %>%
filter(score != 0, scored_by > 10) %>%
group_by("Year" = year) %>%
summarise(avg = round(mean(score, na.rm = T), 2))
highchart() %>%
hc_add_series(data_line_score_avg_mv,
hcaes(x = Year,
y = avg,
color = avg),
type = "line") %>%
hc_title(text = "Average score per year") %>%
hc_xAxis(title = list(text = "Year")) %>%
hc_yAxis(title = list(text = "Average score")) %>%
hc_tooltip(useHTML = T,
borderWidth = 1.5,
headerFormat = "",
pointFormat = paste("{point.Year}
{point.avg}/10")) %>%
hc_legend(enabled = F)
```
### rating MV {.no-title}
```{r, fig.width= 5}
data_bar_rating_mv = data_anime_mv %>%
filter(!is.na(decade)) %>%
group_by("Decade" = decade, rating,
.drop = FALSE) %>%
summarise(Freq = n())
highchart() %>%
hc_add_series(data_bar_rating_mv,
hcaes(x = Decade,
y = Freq,
group = rating),
type = "line") %>%
hc_title(text = "Ratings evolution during decades") %>%
hc_xAxis(title = list(text = "Decade"),
categories = unique(data_bar_rating_mv$Decade)) %>%
hc_yAxis(title = list(text = "Count")) %>%
hc_tooltip(useHTML = T,
borderWidth = 1.5,
headerFormat = "",
pointFormat = paste("{point.rating}
{point.Decade}
{point.Freq}"))
```
### duration MV {.no-title}
```{r, fig.width= 5}
data_bar_duration_mv = data_anime_mv %>%
filter(!is.na(duration)) %>%
mutate(duration = ceiling(duration)) %>%
group_by(duration) %>%
summarise(Freq = n())
highchart() %>%
hc_add_series(data_bar_duration_mv,
hcaes(x = duration,
y = Freq,
color = duration),
type = "column") %>%
hc_title(text = "Movie duration repartition") %>%
hc_xAxis(title = list(text = "Duration (minutes)")) %>%
hc_yAxis(title = list(text = "Count")) %>%
hc_tooltip(useHTML = T,
borderWidth = 1.5,
headerFormat = "",
pointFormat = paste("{point.duration} minutes
{point.Freq} TV animes")) %>%
hc_legend(enabled = F)
```
Row
-----------------------------------------------------------
### Episodes 2 {.no-title}
```{r, fig.width= 5, fig.height= 1}
data_anime_mv_bar_source = data_anime_mv %>%
group_by(source) %>%
summarise(Freq = n()) %>%
arrange(-Freq)
highchart() %>%
hc_add_series(data_anime_mv_bar_source,
hcaes(x = source,
y = Freq,
color = Freq),
type = "bar") %>%
hc_title(text = "Movie sources") %>%
hc_xAxis(categories = data_anime_mv_bar_source$source,
labels = list(style = list(fontSize = 12))) %>%
hc_yAxis(title = list(text = "Count")) %>%
hc_tooltip(useHTML = T,
borderWidth = 1.5,
headerFormat = "",
pointFormat = paste("{point.source}
{point.Freq} movies")) %>%
hc_plotOptions(bar = list(stacking = "normal",
pointPadding = 0,
groupPadding = 0,
borderWidth = 2,
borderColor = "#DBDBDB")) %>%
hc_legend(enabled = FALSE)
```
### density MV {.no-title}
```{r}
data_anime_clean_mv = data_anime_mv %>%
filter(!is.na(decade), score != 0)
densities_mv = map(unique(data_anime_clean_mv$decade), function(x){
dt <- density(data_anime_clean_mv$score[data_anime_clean_mv$decade == x])[1:2]
dt <- list_parse2(as.data.frame(dt))
list(data = dt, name = x)
})
highchart() %>%
hc_add_series_list(densities_mv) %>%
hc_title(text = "Score density per decade") %>%
hc_xAxis(title = list(text = "Score"),
min = 0,
max = 10) %>%
hc_yAxis(title = list(text = "Density")) %>%
hc_tooltip(useHTML = T,
borderWidth = 1.5,
headerFormat = "",
pointFormat = paste("{point.series.name}"))
```
Row
-----------------------------------------------------------
### Most popular Anime Movies {.no-title .bgcolored}
```{r}
data_anime_mv_most_popular = data_anime_mv %>%
filter(popularity != 0) %>%
arrange(popularity) %>%
slice(1:5) %>%
select(anime_id, title, image_url, score, members) %>%
mutate(url_mal = paste("https://myanimelist.net/anime/", anime_id, sep = ""))
```
Most popular Anime Movies
| `r data_anime_mv_most_popular$title[1]` |
`r data_anime_mv_most_popular$title[2]` |
`r data_anime_mv_most_popular$title[3]` |
`r data_anime_mv_most_popular$title[4]` |
`r data_anime_mv_most_popular$title[5]` |
| [{height=200px .imgw}](`r data_anime_mv_most_popular$url_mal[1]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_mv_most_popular$url_mal[2]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_mv_most_popular$url_mal[3]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_mv_most_popular$url_mal[4]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_mv_most_popular$url_mal[5]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
| #1 |
#2 |
#3 |
#4 |
#5 |
| `r format(data_anime_mv_most_popular$members[1], big.mark = ",")` members |
`r format(data_anime_mv_most_popular$members[2], big.mark = ",")` members |
`r format(data_anime_mv_most_popular$members[3], big.mark = ",")` members |
`r format(data_anime_mv_most_popular$members[4], big.mark = ",")` members |
`r format(data_anime_mv_most_popular$members[5], big.mark = ",")` members |
| `r data_anime_mv_most_popular$score[1]`/10 {height=12px} |
`r data_anime_mv_most_popular$score[2]`/10 {height=12px} |
`r data_anime_mv_most_popular$score[3]`/10 {height=12px} |
`r data_anime_mv_most_popular$score[4]`/10 {height=12px} |
`r data_anime_mv_most_popular$score[5]`/10 {height=12px} |
Row
-----------------------------------------------------------
### Most liked Anime Movie {.no-title .bgcolored}
```{r}
data_anime_mv_most_liked = data_anime_mv %>%
filter(rank != 0) %>%
arrange(rank) %>%
slice(1:5) %>%
select(anime_id, title, image_url, score, members) %>%
mutate(url_mal = paste("https://myanimelist.net/anime/", anime_id, sep = ""))
```
Most liked Anime Movies
| `r data_anime_mv_most_liked$title[1]` |
`r data_anime_mv_most_liked$title[2]` |
`r data_anime_mv_most_liked$title[3]` |
`r data_anime_mv_most_liked$title[4]` |
`r data_anime_mv_most_liked$title[5]` |
| [{height=200px .imgw}](`r data_anime_mv_most_liked$url_mal[1]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_mv_most_liked$url_mal[2]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_mv_most_liked$url_mal[3]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_mv_most_liked$url_mal[4]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
[{height=200px .imgw}](`r data_anime_mv_most_liked$url_mal[5]`){target="_blank" rel="noopener noreferrer" title="More details on MyAnimeList website..."}
|
| #1 |
#2 |
#3 |
#4 |
#5 |
| `r format(data_anime_mv_most_liked$members[1], big.mark = ",")` members |
`r format(data_anime_mv_most_liked$members[2], big.mark = ",")` members |
`r format(data_anime_mv_most_liked$members[3], big.mark = ",")` members |
`r format(data_anime_mv_most_liked$members[4], big.mark = ",")` members |
`r format(data_anime_mv_most_liked$members[5], big.mark = ",")` members |
| `r data_anime_mv_most_liked$score[1]`/10 {height=12px} |
`r data_anime_mv_most_liked$score[2]`/10 {height=12px} |
`r data_anime_mv_most_liked$score[3]`/10 {height=12px} |
`r data_anime_mv_most_liked$score[4]`/10 {height=12px} |
`r data_anime_mv_most_liked$score[5]`/10 {height=12px} |
Studio {data-icon="fa-building" data-orientation="rows"}
===========================================================
```{r}
data_dt = data.table(data)
data_dt_expand_studio = data_dt[, list(studio_alone = unlist(strsplit(studio, ", "))), by = names(data_dt)]
freq_studio_type = data_dt_expand_studio %>%
group_by(studio_alone, type,
.drop = F) %>%
summarise(Freq = n()) %>%
filter(type != "Unknown")
freq_studio_type$type = factor(freq_studio_type$type, levels = rev(c("TV", "Movie", "OVA", "ONA", "Special", "Music")))
data_dt_expand_studio_genre = data_dt_expand_studio[, list(genre_alone = unlist(strsplit(genre, ", "))), by = names(data_dt_expand_studio)]
freq_studio_genre = data_dt_expand_studio_genre %>%
group_by(studio_alone, genre_alone,
.drop = F) %>%
summarise(Freq = n()) %>%
arrange(studio_alone, -Freq)
data_dt_expand_studio_public = data_dt_expand_studio %>%
select(studio_alone, rank, title, image_url, type, episodes, aired, duration, score, scored_by, studio)
# stange img behavior on flexdashboard: I can't directly put the html code (pandoc error 99)
# here's a dirty workaround
data_dt_expand_studio_public$image_url = paste0("", sep = "")
data_dt_expand_studio_public$image_url = stringr::str_replace(data_dt_expand_studio_public$image_url, "xyzxyz", "")
data_dt_expand_studio_public = data_dt_expand_studio_public %>%
arrange(rank)
list_genre_order = freq_studio_genre %>%
group_by(genre_alone) %>%
summarise(genre_sum = sum(Freq)) %>%
arrange(-genre_sum)
freq_studio_genre = freq_studio_genre %>%
filter(!is.na(genre_alone)) %>%
left_join(list_genre_order, by = c("genre_alone" = "genre_alone")) %>%
arrange(-genre_sum)
data_dt_expand_studio_public$studio_alone = factor(data_dt_expand_studio_public$studio_alone)
freq_studio_genre$studio_alone = factor(freq_studio_genre$studio_alone)
freq_studio_genre$genre_alone = factor(freq_studio_genre$genre_alone, levels = list_genre_order$genre_alone, ordered = F)
# crosstalk shared data
shared_data_expand_studio <- SharedData$new(data_dt_expand_studio_public, key = ~studio_alone, group = 'Select a Studio...')
shared_data_expand_studio_type <- SharedData$new(freq_studio_type, key = ~studio_alone, group = 'Select a Studio...')
shared_data_expand_studio_genre <- SharedData$new(freq_studio_genre, key = ~studio_alone, group = 'Select a Studio...')
```
Row
-----------------------------------------------------------
```{r}
# preparing 3 plot_ly for subplot
ply1 = plot_ly(data = shared_data_expand_studio_type,
x = ~Freq,
y = ~type,
color = ~type,
text = ~paste(studio_alone, "-", Freq),
colors = c("TV" = "#7fc97f",
"Movie" = "#beaed4",
"OVA" = "#fdc086",
"ONA" = "#ffff99",
"Special" = "#386cb0",
"Music" = "#f0027f"),
opacity = 0.7,
type = "bar",
orientation = "h",
hovertemplate = "%{text}") %>%
layout(barmode = "stack",
xaxis = list(title = "Count"),
annotations = list(text = "Anime Types",
font = list(size = 16),
xref = "paper",
yref = "paper",
xanchor = "center",
yanchor = "bottom",
align = "center",
x = 0.45,
y = 1,
showarrow = F),
margin = list(l = 5, r = 5, b = 50, t = 30, pad = 1),
paper_bgcolor = "#f0f0f0",
plot_bgcolor = "#f0f0f0")
ply2 = plot_ly(data = shared_data_expand_studio,
x = ~scored_by,
y = ~score,
color = ~type,
text = ~paste("Anime title: ", title, "
",
"Studio(s): ", studio, "
",
"Score: ", score, "/10 (#", rank, ")",
sep = ""),
colors = c("TV" = "#7fc97f",
"Movie" = "#beaed4",
"OVA" = "#fdc086",
"ONA" = "#ffff99",
"Special" = "#386cb0",
"Music" = "#f0027f"),
opacity = 0.6,
type = "scatter",
mode = "markers",
hovertemplate = "%{text}") %>%
layout(xaxis = list(range = c(0, (max(data$scored_by)+200000)),
title = "# Reviews"),
yaxis = list(title = "Score"),
annotations = list(text = "Review Scores",
font = list(size = 16),
xref = "paper",
yref = "paper",
xanchor = "center",
yanchor = "bottom",
align = "center",
x = 0.5,
y = 1,
showarrow = F),
margin = list(l = 5, r = 5, b = 50, t = 30, pad = 1),
paper_bgcolor = "#f0f0f0",
plot_bgcolor = "#f0f0f0")
ply3 = plot_ly(data = shared_data_expand_studio_genre,
x = ~Freq,
y = ~genre_alone,
type = "bar",
color = ~genre_alone,
text = ~paste(studio_alone, "-", Freq),
hovertemplate = "%{text}",
orientation = "h") %>%
layout(barmode = "stack",
yaxis = list(title = "",
tickfont = list(size = 8),
categoryorder = "array",
categoryarray = ~Freq,
autorange = "reversed"),
xaxis = list(title = "Count"),
annotations = list(text = "Anime Genres",
font = list(size = 16),
xref = "paper",
yref = "paper",
xanchor = "center",
yanchor = "bottom",
align = "center",
x = 0.5,
y = 1,
showarrow = F),
margin = list(l = 5, r = 5, b = 50, t = 30, pad = 1),
paper_bgcolor = "#f0f0f0",
plot_bgcolor = "#f0f0f0")
```
### studio header selectbar {.no-title .colored}
```{r}
filter_select("sc1", "Select a studio:", shared_data_expand_studio, ~studio_alone, allLevels = TRUE, multiple = FALSE)
```
×
**Note:** 5,930 animes have been removed from the following visualisations because the studio information were missing.
**Disclaimer:** An anime which was co-produced by 2 studios will appear twice for technical purposes. In result, 569 rows have been duplicated. Hence, the following visualisations and table have slightly shifted statistics. However, if you select a studio, the updated visualisations are correct. This tab has to be used to get information from a studio in particular, please refer to the "Overview" tab for general purposes.
Row {data-height = 800}
-----------------------------------------------------------
### three plotly {.no-title}
```{r, fig.height=6}
subplot(ply1,
ply2,
ply3,
widths = c(0.2, 0.4, 0.4),
heights = c(0.9),
margin = c(0.09, 0, 0, 0),
titleX = TRUE,
titleY = TRUE) %>%
layout(showlegend = F) %>%
highlight(on = "plotly_selected",
off = "plotly_deselect",
selected = attrs_selected(opacity = 0.7)) %>%
config(doubleClick = F,
displayModeBar = F)
```
Row
-----------------------------------------------------------
### anime datatable {.no-title .colored}
List of Animes
```{r}
DT::datatable(shared_data_expand_studio,
escape = F,
class = 'cell-border stripe',
rownames = F,
selection = "none",
colnames = c("Rank", "Title", "", "Type", "Episodes", "Aired",
"Duration (mins)", "Score", "Scored by", "Studio"),
options = list(columnDefs = list(list(visible = FALSE, targets = c(0)))))
```
About {data-icon="fa-info-circle"}
===========================================================
Row {data-height=800}
-----------------------------------------------------------
### about txt {.no-title .colored}
Inspiration
* This dashboard was made after seeing tavoosi's incredible interactive dashboard about suicide data (https://www.kaggle.com/tavoosi/suicide-data-full-interactive-dashboard).
* Flexdashboard is a perfect compromise between Rmarkdown reports and Shiny apps. The HTML output can be used without a running R session and loading the dashboard doesn't take time unlike on kaggle.
Data Source
* The dataset used here is from azethoth42's "MyAnimeList Dataset" (https://www.kaggle.com/azathoth42/myanimelist).
* Anime photos are directly loaded from MyAnimeList.net website.
* The main page's illustration has been taken from : https://www.elsetge.cat/pngvi/hmRxih_wallpaper-simple-background-princess-mononoke-no-background/. I couldn't find out the original author.
* The about page's illustration has been taken from : https://detectiveconaninternational.blogspot.com/2017/02/. I couldn't also find out the original author.
Tools used
* The code is written and executed on R language (R markdown script).
* The dashboard has been made with the R package : flexdashboard.
* Visualisations have been produced with highcharter and plotly R packages.
**Do not forget to upvote if you liked this dashboard!**
{height=200px}
