R 计算组中一个点的密度
我正在绘制一些密度曲线,我想在每组的平均值处添加一个点。但是,我想沿着密度曲线的顶部绘制这些点,而不是在0处。有没有办法计算出组内平均点的密度值?代码如下:R 计算组中一个点的密度,r,ggplot2,kernel-density,density-plot,R,Ggplot2,Kernel Density,Density Plot,我正在绘制一些密度曲线,我想在每组的平均值处添加一个点。但是,我想沿着密度曲线的顶部绘制这些点,而不是在0处。有没有办法计算出组内平均点的密度值?代码如下: #制作df df我不确定是否有办法在ggplot geom/stat函数中计算平均值处密度曲线的高度,因此我创建了两个辅助函数来实现这一点 dens_at_mean计算数据平均值处密度曲线的高度get_mean_coords按组运行dens_at_mean,然后缩放高度值以匹配由stat_Halveye生成的y值,并返回可传递到geom_p
#制作df
df我不确定是否有办法在ggplot geom/stat函数中计算平均值处密度曲线的高度,因此我创建了两个辅助函数来实现这一点
dens_at_mean
计算数据平均值处密度曲线的高度get_mean_coords
按组运行dens_at_mean
,然后缩放高度值以匹配由stat_Halveye
生成的y值,并返回可传递到geom_point
的数据帧
# Reproducible data
set.seed(394)
df<- data.frame(group=c("a","b",'c'),
value=rnorm(
3000,
mean=c(1,2,3),
sd=c(1,1.5,1)
))
df %>%
group_by(group)%>%
mutate(mean_value=mean(value)) %>%
# mutate(mean_density = density(mean_value,value))
ggplot()+
aes(x=value,y=group)+
stat_halfeye()+
# could do with stat summary
stat_summary(
orientation = "y",
fun = mean,
geom = "point",
color="blue",
alpha=.8
)+
# or could do with geom_point using precalculated value
# nudged so we can see both.
geom_point(aes(x=mean_value,y=group),
color="red",
position = position_nudge(x=.1)
)
# Reproducible data
set.seed(394)
df<- data.frame(group=c("a","b",'c'),
value=rnorm(
3000,
mean=c(1,2,3),
sd=c(1,1.5,1)
))
# Function to get height of density curve at mean value
dens_at_mean = function(x) {
d = density(x)
mean.x = mean(x)
data.frame(mean.x = mean.x,
max.y = max(d$y),
mean.y = approx(d$x, d$y, xout=mean.x)$y)
}
# Function to return data frame with properly scaled heights
# to plot mean points
get_mean_coords = function(data, value.var, group.var) {
data %>%
group_by({{group.var}}) %>%
summarise(vals = list(dens_at_mean({{value.var}}))) %>%
ungroup %>%
unnest_wider(vals) %>%
# Scale y-value to work properly with stat_halfeye
mutate(mean.y = (mean.y/max(max.y) * 0.9 + 1:n())) %>%
select(-max.y)
}
df %>%
ggplot()+
aes(x=value, y=group)+
stat_halfeye() +
geom_point(data=get_mean_coords(df, value, group),
aes(x=mean.x, y=mean.y),
color="red", size=2) +
theme_bw() +
scale_y_discrete(expand=c(0.08,0.05))