Survey-weighted density plots
We can also explore the shape of a variable with the smooth curve of a density plot. Let's create a density plot of nightly sleep where we facet by gender. Whereas the height of the histogram bars represent counts, the height of the density curve represents probabilities. Therefore, we will need to do some data wrangling before we create the plot.
Latihan ini merupakan bagian dari kursus
Analyzing Survey Data in R
Instruksi latihan
- For
NHANESraw, remove rows that are missingSleepHrsNightorGender. - Grouping by
Gender, add the columnWTMEC4YR_stdwhich equalsWTMEC4YR/sum(WTMEC4YR). - Pipe your wrangled data directly into a
ggplot()whereSleepHrsNightis mapped toxandWTMEC4YR_stdis mapped to weight. Include a densitylayerwithbw = 0.6andfill = "gold"and a facetting layer where you facet byGender.
Latihan interaktif langsung praktik
Cobalah latihan ini dengan melengkapi kode contoh ini.
# Density plot of sleep faceted by gender
NHANESraw %>%
___(!is.na(___), !is.na(___)) %>%
group_by(___) %>%
mutate(WTMEC4YR_std = ___) %>%
ggplot(mapping = aes(x = ___, weight = ___)) +
geom____(bw = 0.6, fill = "gold") +
labs(x = "Hours of Sleep") +
____wrap(~___, labeller = "label_both")