Plus Ultra!
master yeoda
a long, long time ago in a galaxy far, far away
1. Load data
hero <- read.csv("mha_v2.csv", header = TRUE)
head(hero)## ï..Name Occupation Quirk Power Speed Technique Intelligence
## 1 All For One Villain All for One 6.5 6.5 6.5 6.5
## 2 All Might Hero One for All 6.5 6.5 6.0 6.0
## 3 Best Jeanist Hero Fiber Master 2.0 3.0 5.0 2.0
## 4 Bubble Girl Hero Bubble 1.0 2.0 4.5 3.0
## 5 Camie Utsushimi Student Glamour 1.5 2.5 5.0 2.5
## 6 Cementoss Hero Cement 4.5 5.0 5.0 5.0
## Score Rank
## 1 26.0 1
## 2 25.0 2
## 3 12.0 94
## 4 10.5 111
## 5 11.5 105
## 6 19.5 101.1 Rename
names(hero)[1] <- "Name"1.2 Preview
head(hero, 10)## Name Occupation Quirk Power Speed Technique Intelligence
## 1 All For One Villain All for One 6.5 6.5 6.5 6.5
## 2 All Might Hero One for All 6.5 6.5 6.0 6.0
## 3 Best Jeanist Hero Fiber Master 2.0 3.0 5.0 2.0
## 4 Bubble Girl Hero Bubble 1.0 2.0 4.5 3.0
## 5 Camie Utsushimi Student Glamour 1.5 2.5 5.0 2.5
## 6 Cementoss Hero Cement 4.5 5.0 5.0 5.0
## 7 Centipeder Hero Centipede 2.0 4.0 4.0 4.0
## 8 Chronostasis Villain Chronostasis 2.0 2.0 5.0 5.0
## 9 Curious Villain Landmine 2.0 3.0 3.0 4.0
## 10 Dabi Villain Cremation 4.0 3.0 1.5 3.0
## Score Rank
## 1 26.0 1
## 2 25.0 2
## 3 12.0 94
## 4 10.5 111
## 5 11.5 105
## 6 19.5 10
## 7 14.0 63
## 8 14.0 63
## 9 12.0 94
## 10 11.5 1051.3 Data table
library(DT)## Warning: package 'DT' was built under R version 4.0.5datatable(hero,
extensions = "Scroller",
filter = "top",
options = list(scrollX = TRUE,
scrollY = 200))## This version of bslib is designed to work with rmarkdown version 2.7 or higher.2. Aggregate
How many students, heros, and villians are there?
table(hero$Occupation)##
## Hero Jedi Student Villain
## 31 1 53 353. Top 10
Who are the top 10?
hero_top10 <- subset(hero, Rank <= 10)
hero_top10## Name Occupation Quirk Power Speed Technique Intelligence
## 1 All For One Villain All for One 6.5 6.5 6.5 6.5
## 2 All Might Hero One for All 6.5 6.5 6.0 6.0
## 6 Cementoss Hero Cement 4.5 5.0 5.0 5.0
## 17 Endeavor Hero Hellflame 6.5 5.5 5.0 4.0
## 18 Eraser Head Hero Erasure 3.0 4.5 6.5 5.5
## 28 Hawks Hero Fierce Wings 3.5 6.0 6.5 5.0
## 39 Izuku Midoriya Student One for All 5.5 5.0 5.0 5.0
## 43 Katsuki Bakugo Student Explosion 5.0 5.0 5.5 5.0
## 84 Re-Destro Villain Stress 5.5 5.0 5.5 5.0
## 101 Tamaki Amajiki Student Manifest 5.0 4.0 6.0 5.0
## 108 Tomura Shigaraki Villain Decay 6.5 3.5 5.0 5.0
## 120 Yeoda Jedi Force 10.0 10.0 10.0 10.0
## Score Rank
## 1 26.0 1
## 2 25.0 2
## 6 19.5 10
## 17 21.0 3
## 18 19.5 10
## 28 21.0 3
## 39 20.5 6
## 43 20.5 6
## 84 21.0 3
## 101 20.0 8
## 108 20.0 8
## 120 40.0 14. Sort
Sort the results by rank.
hero_top10_sort <- hero_top10[order(hero_top10$Rank),]
hero_top10_sort## Name Occupation Quirk Power Speed Technique Intelligence
## 1 All For One Villain All for One 6.5 6.5 6.5 6.5
## 120 Yeoda Jedi Force 10.0 10.0 10.0 10.0
## 2 All Might Hero One for All 6.5 6.5 6.0 6.0
## 17 Endeavor Hero Hellflame 6.5 5.5 5.0 4.0
## 28 Hawks Hero Fierce Wings 3.5 6.0 6.5 5.0
## 84 Re-Destro Villain Stress 5.5 5.0 5.5 5.0
## 39 Izuku Midoriya Student One for All 5.5 5.0 5.0 5.0
## 43 Katsuki Bakugo Student Explosion 5.0 5.0 5.5 5.0
## 101 Tamaki Amajiki Student Manifest 5.0 4.0 6.0 5.0
## 108 Tomura Shigaraki Villain Decay 6.5 3.5 5.0 5.0
## 6 Cementoss Hero Cement 4.5 5.0 5.0 5.0
## 18 Eraser Head Hero Erasure 3.0 4.5 6.5 5.5
## Score Rank
## 1 26.0 1
## 120 40.0 1
## 2 25.0 2
## 17 21.0 3
## 28 21.0 3
## 84 21.0 3
## 39 20.5 6
## 43 20.5 6
## 101 20.0 8
## 108 20.0 8
## 6 19.5 10
## 18 19.5 105. Scatter plot
Looks like someone is off the charts :-)
hero_top20 <- subset(hero, Rank <= 20)
head(hero_top20)## Name Occupation Quirk Power Speed Technique Intelligence Score
## 1 All For One Villain All for One 6.5 6.5 6.5 6.5 26.0
## 2 All Might Hero One for All 6.5 6.5 6.0 6.0 25.0
## 6 Cementoss Hero Cement 4.5 5.0 5.0 5.0 19.5
## 15 Edgeshot Hero Foldabody 3.5 6.0 5.0 4.0 18.5
## 17 Endeavor Hero Hellflame 6.5 5.5 5.0 4.0 21.0
## 18 Eraser Head Hero Erasure 3.0 4.5 6.5 5.5 19.5
## Rank
## 1 1
## 2 2
## 6 10
## 15 13
## 17 3
## 18 10library(ggplot2)
library(ggrepel)
library(ggpubr)
ggplot(hero_top20) + aes(x = Power, y = Speed) +
geom_point() +
geom_point(data = subset(hero_top20, Name == "Yeoda"),
aes(x = Power ,y = Speed),
color = "red",
size = 5) +
geom_smooth(method = loess) +
geom_label_repel(aes(label = Name),
box.padding = 0.35,
point.padding = 0.8,
segment.color = "blue") +
xlab("Power") + ylab("Speed") +
coord_cartesian(xlim = c(1, 12), ylim = c(1, 12)) +
ggtitle("No tradeoff between power and speed?") +
theme(axis.title.x = element_text(size = 16),
axis.title.y = element_text(size = 16),
axis.text.x = element_text(size = 14),
axis.text.y = element_text(size = 14))
6. Waffle
A breakdown of occupations.
library(dplyr)
hero_occupation <- hero %>%
group_by(Occupation) %>%
summarize(count = n())
hero_occupation## # A tibble: 4 x 2
## Occupation count
## <chr> <int>
## 1 Hero 31
## 2 Jedi 1
## 3 Student 53
## 4 Villain 35hero_occupation <- hero_occupation[c(3, 4, 1, 2),]
hero_occupation## # A tibble: 4 x 2
## Occupation count
## <chr> <int>
## 1 Student 53
## 2 Villain 35
## 3 Hero 31
## 4 Jedi 1hero_occupation_vec <- hero_occupation %>%
pull(count, Occupation)
hero_occupation_vec## Student Villain Hero Jedi
## 53 35 31 1library(waffle)
waffle(hero_occupation_vec,
rows = 5, legend_pos = "bottom")
I am a hero too!
