R中的密度图（ggplot2）由变量着色，返回的分布与直方图和频率图有很大不同吗？

Question

I've combed through several questions on here already and I can't seem to figure out what's happening with my density plots.

I have a set of radiocarbon dates which are attributed to different cultures. I need to display the frequencies of dates through time, but distinguish the dates by culture. A stacked histogram does the job (Fig. 1), but their use is generally discouraged, so that's out of the question, yet I want something smoother than a frequency plot (Fig. 2).

Figure 1: Histogram

Figure 2: Frequency plot

When I produce a density plot coloured by culture (Fig. 3), the relative distribution of the cultures on the y-axis change drastically from their counts. For example, in the density plot, the blue density curve is much higher than that of the purple; yet, in the histogram, we can see that there are way more dates attributed to the purple group.

Figure 3: Density plot

Am I doing something wrong with my code (see below)? Or perhaps I need to scale the density curves in some way? Or is there something about density plots I'm not understanding? (Disclaimer: my knowledge of stats is fairly weak)

Thanks in advance!

ggplot(test, aes(x=CalBP))+
theme_tufte(base_family="sans")+
theme(axis.line=element_line(), axis.text=element_text(color="black")) +
theme(legend.position="none") +
theme(text=element_text(size=14)) +
geom_density(aes(color=factor(Culture), fill=factor(Culture)), alpha = 0.5) +
scale_x_reverse() +
labs(x="Cal. B.P.") +
ylab(expression("Density")) +
coord_cartesian(xlim = c(4773, 225)) +
scale_fill_manual(values=c("#cf9045", "#ebe332", "#5f9388", "#6abeef", "#9d88d6")) +
scale_color_manual(values=c("#cf9045", "#ebe332", "#5f9388", "#6abeef", "#9d88d6")) 

Answer 1

The difference is that a density plot is scaled so that the total area under the curve is 1. It's function is to model a probability density function, which (by definition) has area 1.

If every group in your data had the same number of observations, then the only difference between the density plot and the histogram would be the y-axis. When you have different numbers of observations, the density plot normalizes for this (each will have total area 1), while the bars of the histogram are much higher for the group with more observations.
In base R, you can fix this in the histogram by setting freq = FALSE , but I've not seen density plots scaled up to histograms - it's usually more interesting to ignore the effects of the relative sample sizes.