I am loving using geom_density_ridges(), with individual points also included for each group. However, some groups have small sample sizes (e.g. n=1 or 2) precluding the generation of the density ridges. For these groups, I'd like to be able to plot the locations of the existing observations - even though no probability density function will be shown.
In this example, I'd like to be able to plot the 2 data points for May on the appropriate line.
library(tidyverse)
library(ggridges)
data("lincoln_weather")
#pull weather from all months that are NOT May
lincoln_weather_nomay<-lincoln_weather[which(lincoln_weather$Month!="May"),]
#pull weather just from May
lincoln_weather_may<-lincoln_weather[which(lincoln_weather$Month=="May"),]
#recombine, keeping only the first two rows for the May dataset
new_weather<-rbind(lincoln_weather_nomay,lincoln_weather_may[c(1:2),])
ggplot( new_weather, aes(x=`Min Temperature [F]`,y=Month,fill=Month))+
geom_density_ridges(alpha = 0.5,jittered_points = TRUE, point_alpha=1,point_shape=21) +
labs(x="Average temperature (F)",y='')+
guides(fill=FALSE,color=FALSE)
How can I add the points for the May observations to the appropriate location (i.e. the May slot) and at the appropriate location along the x-axis?
question from:
https://stackoverflow.com/questions/65924548/add-points-to-geom-density-ridges-for-groups-with-small-number-of-observations 与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…