8.6 Exploring pairwise relationships between predictors

Plot a scatterplot with diameter’ vs ‘mass’ with ‘flat’ indicator (fig. 8.2)

scat_flat <- 
     scat %>%
     mutate(flat = ifelse(flat == 1, "yes", "no"))

scat_flat %>% 
     ggplot(aes(col = flat)) + 
     geom_point(aes(x = Diameter, y = Mass), alpha = .5) + 
     geom_rug(data = scat_flat[is.na(scat_flat$Mass),], 
              aes(x = Diameter), 
              sides = "b", 
              lwd = 1)+ 
     geom_rug(data = scat_flat[is.na(scat_flat$Diameter),], 
              aes(y = Mass), 
              sides = "l", 
              lwd = 1) + 
     theme(legend.position = "top")

## Warning: Removed 7 rows containing missing values (`geom_point()`).

scat_flat_NA <- scat %>% 
     mutate(diameter_NA = are_na(Diameter) %>% as.numeric())

cor(scat_flat_NA$flat, scat_flat_NA$diameter_NA)

## [1] 1