Visualizing missingness across two variables

Dealing With Missing Data in R

Nicholas Tierney

Instructor

The problem of visualizing missing data in two dimensions

ggplot(airquality,
       aes(x = Ozone,
           y = Solar.R)) + 
  geom_point()

Warning message:
Removed 42 rows containing 
missing values (geom_point).

ggplot(airquality,
       aes(x = Ozone,
           y = Solar.R)) + 
  geom_miss_point()

ggplot(airquality,
       aes(x = Wind,
           y = Ozone)) + 
  geom_miss_point() + 
  facet_wrap(~ Month)

airquality %>%
  bind_shadow() %>%
ggplot(aes(x = Wind,
           y = Ozone)) + 
  geom_miss_point() + 
  facet_wrap(~ Solar.R_NA)

Dealing With Missing Data in R