How to make scatterplot with geom_jitter plot reproducible?

Question

I am using the Australian AIDS Survival Data. This time to create scatterplots.

To show the genders in survival of different Reported transmission category (T.categ), I plot the chart in this way:

data <- read.csv("https://raw.githubusercontent.com/vincentarelbundock/Rdatasets/master/csv/MASS/Aids2.csv")

data %>%
  ggplot() +
  geom_jitter(aes(T.categ, sex, colour = status))

It shows a chart. But each time I run the code, it seems to produce a different chart. Here are 2 of them putting together.

Anything wrong with the codes? Is it normal (each run a different chart)?

Answer 1

if you use geom_point instead of geom_jitter, you can add position = position_jitter(), which accepts the seed argument:

library(ggplot2)
p <- ggplot(mtcars, aes(as.factor(cyl), disp)) 

p + geom_point(position = position_jitter(seed = 42))

p + geom_point(position = position_jitter(seed = 1))

And back to "42"

p + geom_point(position = position_jitter(seed = 42))

^{Created on 2020-07-02 by the reprex package (v0.3.0)}

Answer 2

Try setting the seed when plotting:

set.seed(1); data %>%
  ggplot() +
  geom_jitter(aes(T.categ, sex, colour = status))

---

From the manual ?geom_jitter:

It adds a small amount of random variation to the location of each point, and is a useful way of handling overplotting caused by discreteness in smaller datasets.

To have that "random variation" reproducible, we need to set set.seed when plotting.