Explore variation by missingness: box plots
Previous exercises use nabular data along with density plots to explore the variation in a variable by the missingness of another.
We are going to use the oceanbuoys dataset from naniar, using box plots instead of facets or others to explore different layers of missingness.
This exercise is part of the course
Dealing With Missing Data in R
Exercise instructions
- Explore the distribution of wind east west (
wind_ew) for the missingness of air temperature usinggeom_boxplot() - Build upon this visualization by faceting by the missingness of humidity (
humidity_NA).
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Explore the distribution of wind east west (`wind_ew`) for
# the missingness of air temperature using `geom_boxplot()`
oceanbuoys %>%
bind_shadow() %>%
ggplot(aes(x = air_temp_c___,
y = ____)) +
geom_____()
# Build upon this visualization by faceting by the missingness of humidity (`humidity_NA`).
oceanbuoys %>%
___() %>%
ggplot(aes(x = ___,
y = ___)) +
geom_____() +
facet_wrap(~___)