block3.

r
# Selecionar variáveis de interesse para análise de agrupamento
data <-  cartola[, c("score_mean", "diff_home_away_s", "score_mean_home",
                     "score_mean_away",  "shots_x_mean", "fouls_mean", "G_mean",
                     "RB_mean",  "PE_mean", "A_mean", "I_mean", "FS_mean")]
names(data) <- 
names(data) <- gsub("_mean", "", names(data))
data <- dummify(data)

# Plotar matriz de correlação
ggcorr(data, geom = "blank", label = TRUE, hjust = 0.75) +
  geom_point(size = 10, aes(color = coefficient > 0, alpha = abs(coefficient) > 0.5)) +
  scale_alpha_manual(values = c("TRUE" = 0.25, "FALSE" = 0)) +
  guides(color = FALSE, alpha = FALSE)