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I have to comute quite long every day and I always try to keep occupied with little
projects. One of my first projects was to increase my knowledge on how to create
R packages. The result of it is Rokemon, a Pokemon/Game Boy inspired package.
In this post, I will briefly introduce some functionalities of the package and illustrate
how incredible useful it can be. A similar introduction can also be found on github.
The package is only available via github so far.
#install.packages(devtools)
devtools::install_github("schochastics/Rokemon")
#used packages
library(Rokemon)
library(tidyverse) # for data wrangling
The Package comes with a dataset on 801 pokemon with a rich set of attributes.
data(pokemon) glimpse(pokemon) ## Observations: 801 ## Variables: 41 ## $ pokedex_number <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1... ## $ name <chr> "Bulbasaur", "Ivysaur", "Venusaur", "Charman... ## $ japanese_name <chr> "Fushigidaneフシギダネ", "Fushigisouフシギソウ", "Fush... ## $ type1 <chr> "grass", "grass", "grass", "fire", "fire", "... ## $ type2 <chr> "poison", "poison", "poison", NA, NA, "flyin... ## $ classfication <chr> "Seed Pokémon", "Seed Pokémon", "Seed Pokémo... ## $ height_m <dbl> 0.7, 1.0, 2.0, 0.6, 1.1, 1.7, 0.5, 1.0, 1.6,... ## $ weight_kg <dbl> 6.9, 13.0, 100.0, 8.5, 19.0, 90.5, 9.0, 22.5... ## $ generation <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,... ## $ is_legendary <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,... ## $ attack <int> 49, 62, 100, 52, 64, 104, 48, 63, 103, 30, 2... ## $ defense <int> 49, 63, 123, 43, 58, 78, 65, 80, 120, 35, 55... ## $ hp <int> 45, 60, 80, 39, 58, 78, 44, 59, 79, 45, 50, ... ## $ speed <int> 45, 60, 80, 65, 80, 100, 43, 58, 78, 45, 30,... ## $ sp_attack <int> 65, 80, 122, 60, 80, 159, 50, 65, 135, 20, 2... ## $ sp_defense <int> 65, 80, 120, 50, 65, 115, 64, 80, 115, 20, 2... ## $ base_total <int> 318, 405, 625, 309, 405, 634, 314, 405, 630,... ## $ abilities <list> [<"Overgrow", "Chlorophyll">, <"Overgrow", ... ## $ capture_rate <int> 45, 45, 45, 45, 45, 45, 45, 45, 45, 255, 120... ## $ experience_growth <int> 1059860, 1059860, 1059860, 1059860, 1059860,... ## $ percentage_male <dbl> 88.1, 88.1, 88.1, 88.1, 88.1, 88.1, 88.1, 88... ## $ base_happiness <int> 70, 70, 70, 70, 70, 70, 70, 70, 70, 70, 70, ... ## $ base_egg_steps <int> 5120, 5120, 5120, 5120, 5120, 5120, 5120, 51... ## $ against_bug <dbl> 1.00, 1.00, 1.00, 0.50, 0.50, 0.25, 1.00, 1.... ## $ against_dark <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,... ## $ against_dragon <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,... ## $ against_electric <dbl> 0.5, 0.5, 0.5, 1.0, 1.0, 2.0, 2.0, 2.0, 2.0,... ## $ against_fairy <dbl> 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 1.0, 1.0, 1.0,... ## $ against_fight <dbl> 0.50, 0.50, 0.50, 1.00, 1.00, 0.50, 1.00, 1.... ## $ against_fire <dbl> 2.0, 2.0, 2.0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5,... ## $ against_flying <dbl> 2.0, 2.0, 2.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,... ## $ against_ghost <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,... ## $ against_grass <dbl> 0.25, 0.25, 0.25, 0.50, 0.50, 0.25, 2.00, 2.... ## $ against_ground <dbl> 1.0, 1.0, 1.0, 2.0, 2.0, 0.0, 1.0, 1.0, 1.0,... ## $ against_ice <dbl> 2.0, 2.0, 2.0, 0.5, 0.5, 1.0, 0.5, 0.5, 0.5,... ## $ against_normal <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,... ## $ against_poison <dbl> 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,... ## $ against_psychic <dbl> 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2,... ## $ against_rock <dbl> 1, 1, 1, 2, 2, 4, 1, 1, 1, 2, 2, 4, 2, 2, 2,... ## $ against_steel <dbl> 1.0, 1.0, 1.0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5,... ## $ against_water <dbl> 0.5, 0.5, 0.5, 2.0, 2.0, 2.0, 0.5, 0.5, 0.5,...
The data comes from Kaggle and was originally scraped from serebii.net.
ggplot2 themes
The package includes three main themes for ggplot.
Theme Rocket
(See what I did there…)
ggplot(pokemon,aes(attack,defense))+
geom_point(col = "grey")+
theme_rocket()+
labs(x = "Jessy",y = "James",
title = "Theme Rocket",
subtitle = "blast off at the speed of light!",
caption = "meowth that's right")
Gamyboy theme
If you want to get nostalgic.
ggplot(pokemon,aes(attack,defense))+ geom_point(shape = 15,col = "#006400",size=2)+ theme_gameboy()+ labs(title = "Classic Gameboy Theme")
If you want to get nostalgic, but not too much, use the Gameboy Advanced theme.
ggplot(pokemon,aes(attack,defense))+ geom_point(shape = 15,col = "#27408B",size=2)+ theme_gba()+ labs(title = "Gameboy Advanced Theme")
Pokemon color pie charts
The color distribution of Pokemon visualized with pie charts have been done before. This code, for example was posted on reddit a while ago.
The Rokemon package implements a similar Algorithm zu dissect the colors of Pokemon.
To make it work, you first need to download all Pokemon sprites. For instance from github.
#basic usage poke_pie(path_to_sprites,pokemon_name)
Let’s look what all time favorite Pikachu looks like.
poke_pie(sprites_path,"pikachu")
Another thing we can do is to compare the starter Pokemon of all 7 generations.
starters <- c("Bulbasaur", "Charmander", "Squirtle",
"Chikorita", "Cyndaquil", "Totodile",
"Treecko", "Torchic", "Mudkip",
"Turtwig", "Chimchar", "Piplup",
"Snivy", "Tepig", "Oshawott",
"Chespin", "Fennekin", "Froakie",
"Rowlet", "Litten", "Popplio")
pies <- list()
k <- 0
for(mon in starters){
k <- k + 1
mon_pie <- poke_pie(sprites_path,mon)
pies[[k]] <- mon_pie
}
gridExtra::grid.arrange(grobs = pies,ncol=3)
It is very interesting how similar in color the first 6 gens are and how the colors seem to explode in gen 7.
Some Use Cases
With the included dataset you can do all kinds of shenanigans. What about a Pokemon type effectiveness chart? Of course with a Pokemon related theme.
pokemon %>%
distinct(type1,.keep_all=TRUE) %>%
select(defender = type1,against_bug:against_water) %>%
gather(attacker,effect,against_bug:against_water) %>%
mutate(attacker = str_replace_all(attacker,"against_","")) %>%
ggplot(aes(y=attacker,x=defender,fill=factor(effect)))+
geom_tile()+
geom_text(aes(label=ifelse(effect!=1,effect,"")))+
scale_fill_manual(values=c("#8B1A1A", "#CD2626", "#EE2C2C",
"#FFFFFF", "#00CD00", "#008B00"))+
theme_rocket(legend.position="none")+
labs(title="Effectiveness Table")
Or why not look at the mean stats of Pokemon types, plotted with the Gameboy theme? Of course with a fitting color theme!
pokemon %>%
group_by(type1) %>%
summarise_at(vars(attack:speed),mean) %>%
gather(stat,value,attack:speed) %>%
ggplot(aes(x=type1,y=value,fill=type1))+
geom_col()+
scale_fill_poketype(name="")+
facet_wrap(~stat)+
theme_gameboy()+
guides(fill = guide_legend(ncol = 9))+
theme(axis.text.x = element_blank(),
axis.ticks.x= element_blank())+
labs(x="",y="")
The package includes some more functions and color palettes. To use them, checkout the README of the github repo.
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