Yu-Gi-Oh

Yu-Gi-Oh the card game, the game of strategy, mind tricks, spells and traps.

Data Source - Yu-Gi-Oh! Cards

1 - Preping our enviornment

Starting off we want to prep our work area with the libraries we want to use and the data that we will be using.

1.1 - Setting up tidyverse

library(tidyverse)

Registered S3 methods overwritten by 'dbplyr':
  method         from
  print.tbl_lazy     
  print.tbl_sql      
── Attaching packages ─────────────── tidyverse 1.3.1 ──
✓ ggplot2 3.3.3     ✓ purrr   0.3.4
✓ tibble  3.1.1     ✓ dplyr   1.0.5
✓ tidyr   1.1.3     ✓ stringr 1.4.0
✓ readr   1.4.0     ✓ forcats 0.5.1
── Conflicts ────────────────── tidyverse_conflicts() ──
x dplyr::filter() masks stats::filter()
x dplyr::lag()    masks stats::lag()

1.2 - Getting our data

data <- read.csv('cards.csv')
head(data)

2 - Overview

summary(data)

       id                name          
 Min.   :    10000   Length:11183      
 1st Qu.: 24466676   Class :character  
 Median : 49511705   Mode  :character  
 Mean   : 51356349                     
 3rd Qu.: 74892018                     
 Max.   :501000007                     
                                       
     type               desc                atk      
 Length:11183       Length:11183       Min.   :   0  
 Class :character   Class :character   1st Qu.: 800  
 Mode  :character   Mode  :character   Median :1500  
                                       Mean   :1464  
                                       3rd Qu.:2100  
                                       Max.   :5000  
                                       NA's   :3797  
      def           level            race          
 Min.   :   0   Min.   : 0.000   Length:11183      
 1st Qu.: 500   1st Qu.: 3.000   Class :character  
 Median :1200   Median : 4.000   Mode  :character  
 Mean   :1225   Mean   : 4.501                     
 3rd Qu.:1800   3rd Qu.: 6.000                     
 Max.   :5000   Max.   :13.000                     
 NA's   :4126   NA's   :4127                       
  attribute             scale         archetype        
 Length:11183       Min.   : 0.000   Length:11183      
 Class :character   1st Qu.: 2.000   Class :character  
 Mode  :character   Median : 4.000   Mode  :character  
                    Mean   : 4.381                     
                    3rd Qu.: 7.000                     
                    Max.   :13.000                     
                    NA's   :10905                      
    linkval      linkmarkers         image_url        
 Min.   :1.000   Length:11183       Length:11183      
 1st Qu.:2.000   Class :character   Class :character  
 Median :2.000   Mode  :character   Mode  :character  
 Mean   :2.383                                        
 3rd Qu.:3.000                                        
 Max.   :6.000                                        
 NA's   :10854                                        
 image_url_small      ban_tcg         
 Length:11183       Length:11183      
 Class :character   Class :character  
 Mode  :character   Mode  :character  
                                      
                                      
                                      
                                      
   ban_ocg            ban_goat        
 Length:11183       Length:11183      
 Class :character   Class :character  
 Mode  :character   Mode  :character  
                                      
                                      
                                      
                                      

By just giving our data the glance over we can tell that there are a total of 11,183 cards currently in the TCG and OCG.

• These are the key questions that we want answered
  • Which card has the longest desc, on average how long are card desc?
  • What is the average Atk and Def for each level of monster?

3 - Exploring Data

unique(data$type)

 [1] "Spell Card"                     
 [2] "Effect Monster"                 
 [3] "Normal Monster"                 
 [4] "Flip Effect Monster"            
 [5] "Trap Card"                      
 [6] "Union Effect Monster"           
 [7] "Fusion Monster"                 
 [8] "Pendulum Effect Monster"        
 [9] "Link Monster"                   
[10] "XYZ Monster"                    
[11] "Synchro Tuner Monster"          
[12] "Tuner Monster"                  
[13] "Synchro Monster"                
[14] "Gemini Monster"                 
[15] "Normal Tuner Monster"           
[16] "Spirit Monster"                 
[17] "Ritual Effect Monster"          
[18] "Token"                          
[19] "Skill Card"                     
[20] "Ritual Monster"                 
[21] "Toon Monster"                   
[22] "Pendulum Normal Monster"        
[23] "Synchro Pendulum Effect Monster"
[24] "Pendulum Tuner Effect Monster"  
[25] "XYZ Pendulum Effect Monster"    
[26] "Pendulum Effect Fusion Monster" 
[27] "Pendulum Flip Effect Monster"   

We can observe that there are 27 different types of cards that are utilized in game.

unique(data$attribute)

[1] ""       "EARTH"  "WATER"  "WIND"   "DARK"  
[6] "LIGHT"  "FIRE"   "DIVINE"

Monster cards have these attributes, while other types of cards do not.

data$attribute[data$attribute == ""] <- "NONE"

Normally Cards with no attribute will appear as blank for visualization purposes I transformed them into a readable variable.

ggplot(data = data) +
  geom_bar(mapping = aes(type), stat = "count", fill='#606c38', colour = '#283618') +
  theme(axis.text.x = element_text(angle = 50, vjust = 1, hjust = 1))

Looks like Effect Monsters are the most produced by a large margin, almost double the amount of spell cards which are the second most produced card.

ggplot(data = data) +
  geom_bar(mapping = aes(attribute), stat = "count", fill='#dda15e', colour = '#bc6c25') +
  theme(axis.text.x = element_text(angle = 50, vjust = 1, hjust = 1))

The most common attribute (Not counting spells, traps and tokens) in the game is DARK, second EARTH, third LIGHT, the rest are equally not as used in the game and DIVINE is only used in special cards.

4 - Answering our questions

4.1 - Which card has the longest desc, on average how long are card desc?

data$desc_length <- str_length(str_replace_all(data$desc, " ", ""))

Here we want to count each of the characters not including spaces.

mean(data$desc_length)

[1] 225.0753

Each card’s description has an average of 225.07 letters. In the English language words average 4.7 letters in length. This would mean that in general each card has 47.88 words.

subset(data, desc_length == max(desc_length))

The Yu-Gi-Oh card with the longest description with 73 for the top portion and 107 for the bottom text adding up to 180 words in total.

4.2 - What is the average Atk and Def for each level of monster?

Logically we would assume that depending on the level of the monster the Atk and/or Def would increase.

ggplot(data = data, aes(y = level)) +
  geom_smooth(aes(x = atk, colour = "Attack")) + 
  geom_smooth(aes(x = def, colour = "Defense")) +
  labs(
    x = "Atk and Def (0 - 5000)",
    y = "Monster's Level (0 - 13)",
    colour = "Legend"
       ) +
  ylim(0, NA)

Through this chart we can see that higher levels have generally high Attack and Defense, this would seem obvious but could be a trap that a card game may fall through during many years in their run.

5 - What does it mean?

In the end we can see that despite all the years and all the cards created Yu-Gi-Oh has managed to stay balanced with few banned cards here and there.

Though one problem that surged is that due to the increase in effect monsters cards and the fact that on average cards have a lot of words, which could deter newer players from wanting to pick up the game.