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.
Bu egzersiz, kursun bir parçasıdır
Dealing With Missing Data in R
Egzersiz talimatları
- 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).
Uygulamalı etkileşimli egzersiz
Bu egzersizi bu örnek kodu tamamlayarak deneyin.
# 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(~___)