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.
Deze oefening maakt deel uit van de cursus
Dealing With Missing Data in R
Oefeninstructies
- 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).
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# 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(~___)