R, ggplot, How do I keep related points together when using jitter?

Question

One of the variables in my data frame is a factor denoting whether an amount was gained or spent. Every event has a "gain" value; there may or may not be a corresponding "spend" amount. Here is an image with the observations overplotted:

Adding some random jitter helps visually, however, the "spend" amounts are divorced from their corresponding gain events:

I'd like to see the blue circles "bullseyed" in their gain circles (where the "id" are equal), and jittered as a pair. Here are some sample data (three days) and code:

library(ggplot2)
ccode<-c(Gain="darkseagreen",Spend="darkblue")
ef<-data.frame(
  date=as.Date(c("2021-03-01","2021-03-01","2021-03-01","2021-03-01","2021-03-01","2021-03-01","2021-03-01","2021-03-01","2021-03-02","2021-03-02","2021-03-02","2021-03-02","2021-03-02","2021-03-02","2021-03-02","2021-03-03","2021-03-03","2021-03-03","2021-03-03","2021-03-03","2021-03-03","2021-03-03","2021-03-03","2021-03-01","2021-03-01","2021-03-01","2021-03-01","2021-03-01","2021-03-01","2021-03-01","2021-03-01","2021-03-02","2021-03-02","2021-03-02","2021-03-02","2021-03-02","2021-03-02","2021-03-02","2021-03-03","2021-03-03","2021-03-03","2021-03-03","2021-03-03","2021-03-03","2021-03-03","2021-03-03")),
  site=c("Castle","Temple","Temple","Temple","Temple","Temple","Palace","Palace","Castle","Castle","Castle","Temple","Temple","Palace","Palace","Castle","Castle","Castle","Castle","Castle","Temple","Temple","Palace","Castle","Temple","Temple","Temple","Temple","Temple","Palace","Palace","Castle","Castle","Castle","Temple","Temple","Palace","Palace","Castle","Castle","Castle","Castle","Castle","Temple","Temple","Palace"),
  id=c("C123","T101","T93","T94","T95","T96","P102","P96","C126","C127","C128","T100","T98","P100","P98","C129","C130","C131","C132","C133","T104","T99","P99","C123","T101","T93","T94","T95","T96","P102","P96","C126","C127","C128","T100","T98","P100","P98","C129","C130","C131","C132","C133","T104","T99","P99"),
  gainspend=c("Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Gain","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend","Spend"),
  amount=c(6,14,34,31,3,10,6,14,2,16,16,14,1,1,15,11,8,7,2,10,15,4,3,NA,NA,4,5,NA,NA,NA,NA,NA,NA,2,NA,1,NA,3,NA,NA,2,NA,NA,2,NA,3))
#▼ 3 day, points centered
ggplot(ef,aes(date,site)) + 
  geom_point(aes(size=amount,color=gainspend),alpha=0.5) +
  scale_color_manual(values=ccode) +
  scale_size_continuous(range=c(1,15),breaks=c(5,10,20))
#▼ 3 day, jitted
ggplot(ef,aes(date,site)) + 
  geom_point(aes(size=amount,color=gainspend),alpha=0.5,position=position_jitter(w=0,h=0.2)) +
  scale_color_manual(values=ccode) +
  scale_size_continuous(range=c(1,15),breaks=c(5,10,20))

Answer 1

My main idea is the old "add jitter manually" approach. I'm wondering if a nicer approach could be something like plotting little pie charts as points a la package scatterpie.

In this case you could add a random number for the amount of jitter to each ID so points within groups will be moved the same amount. This takes doing work outside of ggplot2.

First, draw the "jitter" to add for each ID. Since a categorical axis is 1 unit wide, I choose numbers between -.3 and .3. I use dplyr for this work and set the seed so you will get the same results.

library(dplyr)
set.seed(16)
ef2 = ef %>%
    group_by(id) %>%
    mutate(jitter = runif(1, min = -.3, max = .3)) %>%
    ungroup()

Then the plot. I use a geom_blank() layer so that the categorical site axis is drawn before I add the jitter. I convert site to be numeric from a factor and add the jitter on; this only works for factors so luckily categorical axes in ggplot2 are based on factors.

Now paired ID's move together.

ggplot(ef2, aes(x = date, y = site)) + 
    geom_blank() +
    geom_point(aes(size = amount, color = gainspend, 
                   y = as.numeric(factor(site)) + jitter),
               alpha=0.5) +
    scale_color_manual(values = ccode) +
    scale_size_continuous(range = c(1, 15), breaks = c(5, 10, 20))
#> Warning: Removed 15 rows containing missing values (geom_point).

^{Created on 2021-09-23 by the reprex package (v2.0.0)}