World of Warcraft:Legion bgs
Carlos Rosales
2025-02-14
Abstract: En este proyecto se analizarán algunas métricas interesantes, tales como, cantidad de jugares por facción, tendencia de clases, tasa de promedio de victorias por mapa. Se utilizó el dataset World of Warcraft Battlegrounds extraído de kaggle, el autor Carlos Blesa, toma una muestra interesante de datos en Battlegrounds desarrolladas en la expansión de Legión
Se verá la cantidad y el porcentaje de jugadores de alianza y horda que participaron en las bgs de Legion
ggplot(wow_battlegrouds_final, aes(x = Faction)) +
geom_bar(aes(fill = Faction), stat = "count") +
geom_text(aes(label = paste(round(after_stat(count), 0),
" (", round(..count../sum(..count..)*100, 1), "%)", sep = "")),
stat = "count", vjust = 1.1, position = position_stack(vjust = 1.1)) +
scale_fill_manual(values = c("Alliance" = "blue", "Horde" = "red"))## Warning: The dot-dot notation (`..count..`) was deprecated in ggplot2 3.4.0.
## ℹ Please use `after_stat(count)` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
Luego vemos la cantidad de jugadores por clase en las bgs
ggplot(wow_battlegrouds_final)+
geom_bar(mapping = aes(x=Class, fill = Class))+
geom_text(mapping = aes(x=Class,y=..count..,label = ..count..)
,stat = "count",vjust=1.1)+
scale_fill_manual(values = c( "Death Knight" = "red",
"Demon Hunter" = "darkmagenta",
"Druid" = "orange",
"Hunter" = "green",
"Mage" = "skyblue",
"Monk" = "springgreen",
"Paladin" = "pink",
"Priest" = "white",
"Rogue" = "yellow",
"Shaman" = "blue",
"Warlock" = "purple",
"Warrior" = "tan"))+
theme(axis.text.x = element_text(angle = 45, hjust = 1))
Veremos la cantidad de healers y dps que participaron en las batallas
wow_battlegrouds_final %>%
count(Class, Rol) %>%
ggplot(aes(x = Rol, y = n, fill = Class)) +
geom_col(position = "stack") +
geom_text(aes(x = Rol, y = n, label = n),
position = position_stack(vjust = 0.5), color = "black", size = 3) +
scale_fill_manual(values = c(
"Death Knight" = "red",
"Demon Hunter" = "darkmagenta",
"Druid" = "orange",
"Hunter" = "green",
"Mage" = "skyblue",
"Monk" = "springgreen",
"Paladin" = "pink",
"Priest" = "white",
"Rogue" = "yellow",
"Shaman" = "blue",
"Warlock" = "purple",
"Warrior" = "tan"
)) +
labs(title = "Roles y Clases", x = "Rol", y = "Conteo")
#### Veremos una tabla con la distribución de clases por la horda
## # A tibble: 12 × 12
## Class AB BG DG ES SA SM SS TK TP WG Total
## <chr> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <dbl>
## 1 Death Knig… 22 57 11 44 14 30 8 40 27 54 307
## 2 Demon Hunt… 19 53 10 42 8 39 11 61 28 59 330
## 3 Druid 38 53 12 38 28 52 12 55 31 62 381
## 4 Hunter 23 59 10 36 19 57 16 28 40 63 351
## 5 Mage 35 62 17 44 15 46 12 67 36 48 382
## 6 Monk 24 14 8 18 7 26 5 25 14 34 175
## 7 Paladin 34 62 17 30 12 49 15 38 35 64 356
## 8 Priest 38 47 12 49 17 61 13 38 45 64 384
## 9 Rogue 49 82 13 44 8 46 9 63 32 36 382
## 10 Shaman 64 115 20 55 26 112 20 98 76 120 706
## 11 Warlock 26 69 6 29 21 64 12 57 35 64 383
## 12 Warrior 30 79 12 34 15 55 6 77 42 92 442También se muestran datos con la distribución para la alianza
## # A tibble: 12 × 12
## Class AB BG DG ES SA SM SS TK TP WG Total
## <chr> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <dbl>
## 1 Death Knig… 19 41 7 21 13 40 10 36 26 50 263
## 2 Demon Hunt… 21 59 7 51 7 50 3 48 40 54 340
## 3 Druid 48 90 26 63 22 85 17 75 47 78 551
## 4 Hunter 35 78 14 46 16 86 16 53 52 77 473
## 5 Mage 46 61 16 28 24 54 17 71 43 72 432
## 6 Monk 24 36 3 27 11 29 4 29 23 38 224
## 7 Paladin 33 81 16 36 20 66 17 82 37 66 454
## 8 Priest 41 49 18 30 17 60 18 31 42 79 385
## 9 Rogue 29 46 6 35 16 48 6 56 40 74 356
## 10 Shaman 30 45 17 36 14 36 8 38 20 34 278
## 11 Warlock 25 56 10 26 15 31 13 48 31 58 313
## 12 Warrior 48 80 10 54 20 48 11 69 47 74 461También se pueden ver las clases utilizadas en todas las bgs separados por facción
ggplot(wow_battlegrouds_final, aes(x = Class, fill = Class)) +
geom_bar(mapping = aes(x = Class, fill = Class)) +
geom_text(mapping = aes(x = Class, y = ..count.., label = ..count..),
stat = "count", vjust = 1) +
facet_wrap(~ Faction) +
scale_fill_manual(values = c(
"Death Knight" = "red",
"Demon Hunter" = "darkmagenta",
"Druid" = "orange",
"Hunter" = "green",
"Mage" = "skyblue",
"Monk" = "springgreen",
"Paladin" = "pink",
"Priest" = "white",
"Rogue" = "yellow",
"Shaman" = "blue",
"Warlock" = "purple",
"Warrior" = "tan"
)) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
Añadiremos también los dps y healers que participaron por cada facción
wow_battlegrouds_final %>%
count(Faction, Rol, Class) %>%
ggplot(aes(x = Faction, y = n, fill = Class)) +
geom_col(position = "stack") +
geom_text(aes(x = Faction, y = n, label = n),
position = position_stack(vjust = 0.5), color = "black", size = 3) +
facet_wrap(~ Rol) +
scale_fill_manual(values = c(
"Death Knight" = "red",
"Demon Hunter" = "darkmagenta",
"Druid" = "orange",
"Hunter" = "green",
"Mage" = "skyblue",
"Monk" = "springgreen",
"Paladin" = "pink",
"Priest" = "white",
"Rogue" = "yellow",
"Shaman" = "blue",
"Warlock" = "purple",
"Warrior" = "tan"
)) +
labs(title = "Facciones, Roles y Clases", x = "Facción", y = "Conteo")
Por último podemos ver el winrate de cada facción por cada Battleground donde:
AB = Arathi basin BG = Battle for Gilneas DG = Deepwind Gorge ES = Eye of the storm SA = Strand of the Acients SM = Silvershard Mines SS = Seething shore TK = Temple of Kotmogu TP = Twin Peaks WG = Warsong Gulch
wow_battlegrouds_final %>%
group_by(Faction, Battleground) %>%
summarise(tasa_victoria = sum(Win) / n() * 100,.groups = "drop_last") %>%
ggplot(aes(x = Battleground, y = tasa_victoria, fill = Faction)) +
geom_col(position = "dodge") +
geom_text(aes(label = paste0(round(tasa_victoria), "%")),
position = position_dodge(width = 1), vjust = -0.5) +
scale_fill_manual(labels = c("Alianza", "Horda"), values = c("blue", "red")) +
labs(title = "Tasa de victoria por facción y mapa", x = "Mapa",
y = "Tasa de victoria (%)", fill = "Facción") +
theme_classic()
Además podemos chequear la tasa promedio de victoria de la horda
wow_battlegrouds_final %>%
filter(Faction == "Horde" & Win == 1) %>%
summarise(tasa_victoria_promedio = n() / nrow(filter(wow_battlegrouds_final,
Faction == "Horde"))) * 100## tasa_victoria_promedio
## 1 64.79581Ahora la tasa promedio de victoria para la alianza
wow_battlegrouds_final %>%
filter(Faction == "Alliance" & Win == 1) %>%
summarise(tasa_victoria_promedio = n() / nrow(filter(wow_battlegrouds_final,
Faction == "Alliance"))) * 100## tasa_victoria_promedio
## 1 36.31347Ahora veremos la tasa de derrotas entre ambas facciones
wow_battlegrouds_final %>%
group_by(Faction, Battleground) %>%
summarise(tasa_derrota = sum(Lose) / n() * 100,.groups = "drop_last") %>%
ggplot(aes(x = Battleground, y = tasa_derrota, fill = Faction)) +
geom_col(position = "dodge") +
geom_text(aes(label = paste0(round(tasa_derrota), "%")),
position = position_dodge(width = 1), vjust = -0.5) +
scale_fill_manual(labels = c("Alianza", "Horda"), values = c("blue", "red")) +
labs(title = "Tasa de derrota por facción y mapa", x = "Mapa",
y = "Tasa de Derrota (%)", fill = "Facción") +
theme_classic()
Se verificará la tasa promedio de derrotas por facción
wow_battlegrouds_final %>%
filter(Faction == "Horde" & Lose == 1) %>%
summarise(tasa_derrota_promedio = n() / nrow(filter(wow_battlegrouds_final,
Faction == "Horde"))) * 100## tasa_derrota_promedio
## 1 35.20419Lo mismo con la alianza
wow_battlegrouds_final %>%
filter(Faction == "Alliance" & Lose == 1) %>%
summarise(tasa_derrota_promedio = n() / nrow(filter(wow_battlegrouds_final,
Faction == "Alliance"))) * 100## tasa_derrota_promedio
## 1 63.68653