STAT410 Week 1
Steven
2026-02-27
- Optional if pokemon isn’t already installed
#install.packages("pokemon")Load relevant libraries
library(dplyr) ##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(tidyr)
library(ggplot2)
library(gt)## Warning: package 'gt' was built under R version 4.5.2Import pokemon dataset and name the data frame allpokemon
allpokemon <- pokemon::pokemonA quick glance at the dataframe
?pokemon## starting httpd help server ... donehead(allpokemon)## # A tibble: 6 × 22
## id pokemon species_id height weight base_experience type_1 type_2 hp
## <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <chr> <chr> <dbl>
## 1 1 bulbasaur 1 0.7 6.9 64 grass poison 45
## 2 2 ivysaur 2 1 13 142 grass poison 60
## 3 3 venusaur 3 2 100 236 grass poison 80
## 4 4 charmander 4 0.6 8.5 62 fire <NA> 39
## 5 5 charmeleon 5 1.1 19 142 fire <NA> 58
## 6 6 charizard 6 1.7 90.5 240 fire flying 78
## # ℹ 13 more variables: attack <dbl>, defense <dbl>, special_attack <dbl>,
## # special_defense <dbl>, speed <dbl>, color_1 <chr>, color_2 <chr>,
## # color_f <chr>, egg_group_1 <chr>, egg_group_2 <chr>, url_icon <chr>,
## # generation_id <dbl>, url_image <chr>tail(allpokemon)## # A tibble: 6 × 22
## id pokemon species_id height weight base_experience type_1 type_2 hp
## <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <chr> <chr> <dbl>
## 1 10142 minior-vio… 774 0.3 0.3 175 rock flying 60
## 2 10143 mimikyu-bu… 778 0.2 0.7 167 ghost fairy 55
## 3 10144 mimikyu-to… 778 0.4 2.8 167 ghost fairy 55
## 4 10145 mimikyu-to… 778 0.4 2.8 167 ghost fairy 55
## 5 10146 kommo-o-to… 784 2.4 208. 270 dragon fight… 75
## 6 10147 magearna-o… 801 1 80.5 120 steel fairy 80
## # ℹ 13 more variables: attack <dbl>, defense <dbl>, special_attack <dbl>,
## # special_defense <dbl>, speed <dbl>, color_1 <chr>, color_2 <chr>,
## # color_f <chr>, egg_group_1 <chr>, egg_group_2 <chr>, url_icon <chr>,
## # generation_id <dbl>, url_image <chr>summary(allpokemon)## id pokemon species_id height
## Min. : 1 Length:949 Min. : 1.0 Min. : 0.100
## 1st Qu.: 238 Class :character 1st Qu.:191.0 1st Qu.: 0.500
## Median : 475 Mode :character Median :395.0 Median : 1.000
## Mean : 1900 Mean :400.1 Mean : 1.228
## 3rd Qu.: 712 3rd Qu.:615.0 3rd Qu.: 1.500
## Max. :10147 Max. :802.0 Max. :14.500
##
## weight base_experience type_1 type_2
## Min. : 0.10 Min. : 36.0 Length:949 Length:949
## 1st Qu.: 8.50 1st Qu.: 68.0 Class :character Class :character
## Median : 28.80 Median :157.0 Mode :character Mode :character
## Mean : 66.21 Mean :150.5
## 3rd Qu.: 66.60 3rd Qu.:184.0
## Max. :999.90 Max. :608.0
##
## hp attack defense special_attack
## Min. : 1.00 Min. : 5.00 Min. : 5.00 Min. : 10.00
## 1st Qu.: 50.00 1st Qu.: 55.00 1st Qu.: 50.00 1st Qu.: 50.00
## Median : 65.00 Median : 75.00 Median : 70.00 Median : 65.00
## Mean : 68.95 Mean : 79.47 Mean : 74.07 Mean : 72.81
## 3rd Qu.: 80.00 3rd Qu.:100.00 3rd Qu.: 90.00 3rd Qu.: 95.00
## Max. :255.00 Max. :190.00 Max. :230.00 Max. :194.00
##
## special_defense speed color_1 color_2
## Min. : 20.00 Min. : 5.00 Length:949 Length:949
## 1st Qu.: 50.00 1st Qu.: 45.00 Class :character Class :character
## Median : 70.00 Median : 65.00 Mode :character Mode :character
## Mean : 72.22 Mean : 69.02
## 3rd Qu.: 90.00 3rd Qu.: 90.00
## Max. :230.00 Max. :180.00
##
## color_f egg_group_1 egg_group_2 url_icon
## Length:949 Length:949 Length:949 Length:949
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## generation_id url_image
## Min. :1.000 Length:949
## 1st Qu.:2.000 Class :character
## Median :4.000 Mode :character
## Mean :3.695
## 3rd Qu.:5.000
## Max. :7.000
## NA's :147After running the above code I noticed a few things:
- 147 pokemon with NA for generation_id (upon viewing the dataframe noted that they were special pokemon that I didn't want in my results)
- There was no total stat points column for each pokemon which I was really interested in (This is what I was going to test to determine each pokemon types overall strength)
- type_1 was primary typing and type_2 was secondary type if it had one (since I want to plot total stats based on typing I will need to count some pokemon for both types)Therefore I used dplyr filter to remove pokemon which had NA for generation_id Then I used dplyr mutate to create the total stat points for each pokemon
filteredpokemon <- allpokemon |> filter(!is.na(generation_id))
pokemonwtotal <- filteredpokemon |>
mutate(total_stats = (hp + attack + defense + special_attack + special_defense
+ speed) )Here I took some advice from week 2 lab and used pivot_longer to essentially add the type_1 and type_2 values. This results in some of the pokemon being listed twice but that’s ok for my purposes as I’m most interested in the relationship between typing (type) and overall strength (total_stats).
pokemoncombinedtypes <- pokemonwtotal |>
pivot_longer(
cols = c(type_1, type_2),
names_to = "primary/secondary",
values_to = "type") |>
filter(!is.na(type))Next I tried a selection of graph types but settled on the boxplot which looks the neatest in my opinion (Especially since I wanted to display a comparison of the general strength of each type of pokemon someone would encounter in the wild). I also added colour coding, labels, and manually added a scale I thought would be most helpful (inputting the custom scale was a surprise for me and took longer than expected as I thought it was something I could add in theme(), but ggplot2 documentation was really helpful: https://ggplot2-book.org/)
ggplot(pokemoncombinedtypes, aes(y = type, x = total_stats, col = type)) +
geom_boxplot() +
scale_x_continuous(breaks = c(200, 300, 400, 500, 600, 700)) +
theme_bw() +
labs(x = "Total Stat Points", y = "Type", title = "The Strength of Different Pokemon Types") +
theme(plot.title = element_text(face = "bold", hjust= 0.5, size = 16),
axis.title.y = element_text(face = "bold", size = 12),
axis.title.x = element_text(face = "bold", size = 12),
legend.position = "none")
Next I used dplyr to pull out the 6 strongest pokemon of each type (the most you can have in a party).
top6bytype <- pokemoncombinedtypes |>
group_by(type) |>
slice_max(order_by = total_stats, n = 6, with_ties = FALSE)Then I created a data frame for party stats, summing the stats of all 6 pokemon of each type to get the total party strength. (This step was more challenging than I thought it would be as I had sep = “,” instead of collapse = “,” and couldn’t work out where I went wrong for a while)
party_stats <- top6bytype |>
group_by(type) |>
summarise(party_total_stats = sum(total_stats, na.rm = TRUE),
Party_Members = paste(pokemon, collapse = ", ")) |>
arrange(desc(party_total_stats))Finally, I took the party stats data frame and converted it into a table with gt and played around with the table style, especially different colours, before settling with an easier to read alternating grey and the default white scheme
party_stats |>
gt(auto_align = FALSE) |>
tab_header(
title = "Best Parties Attainable for Each Type",
subtitle = "(The Ultimate Guide for Gym Leaders)"
) |>
tab_style(
style = cell_fill(color = "grey90"),
locations = cells_body(
rows = seq(1, nrow(party_stats), 2)
)
) | Best Parties Attainable for Each Type | ||
| (The Ultimate Guide for Gym Leaders) | ||
| type | party_total_stats | Party_Members |
|---|---|---|
| dragon | 4080 | rayquaza, dialga, palkia, giratina-altered, reshiram, zekrom |
| flying | 3920 | lugia, ho-oh, rayquaza, yveltal, dragonite, salamence |
| psychic | 3920 | mewtwo, lugia, solgaleo, lunala, mew, celebi |
| normal | 3770 | arceus, slaking, regigigas, meloetta-aria, silvally, snorlax |
| steel | 3760 | dialga, solgaleo, metagross, jirachi, heatran, genesect |
| fire | 3740 | ho-oh, reshiram, heatran, victini, volcanion, moltres |
| water | 3710 | palkia, kyogre, manaphy, volcanion, suicune, keldeo-ordinary |
| ghost | 3615 | giratina-altered, lunala, hoopa, marshadow, decidueye, dusknoir |
| fairy | 3590 | xerneas, diancie, magearna, tapu-koko, tapu-lele, tapu-bulu |
| dark | 3580 | yveltal, tyranitar, darkrai, hydreigon, guzzlord, greninja |
| electric | 3560 | zekrom, zapdos, raikou, thundurus-incarnate, tapu-koko, xurkitree |
| ground | 3540 | groudon, garchomp, landorus-incarnate, zygarde, swampert, rhyperior |
| fighting | 3520 | kommo-o, marshadow, cobalion, terrakion, virizion, keldeo-ordinary |
| rock | 3497 | tyranitar, diancie, regirock, terrakion, nihilego, archeops |
| grass | 3455 | celebi, shaymin-land, virizion, tapu-bulu, kartana, tangrowth |
| ice | 3420 | kyurem, articuno, regice, lapras, vanilluxe, walrein |
| bug | 3335 | genesect, buzzwole, pheromosa, volcarona, golisopod, yanmega |
| poison | 3165 | nihilego, crobat, venusaur, tentacruel, roserade, nidoqueen |