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.
Bu egzersiz
Analyzing Survey Data in R
kursunun bir parçasıdırEgzersiz talimatları
- 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.
Uygulamalı interaktif egzersiz
Bu örnek kodu tamamlayarak bu egzersizi bitirin.
# 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")