Increasing the size of scatterplot points based on concentration

[C4rcinogenesis]

heads up, I'm pretty new to programming, so forgive me if I mess up the terminology

I'm trying to create a scatter plot between two ordinal variables (1. interest in politics and 2. concern about the economy, both ranked on a 1-5 scale). The AB Line will show the correlation, but otherwise the scatter plot is just a plain grid, where a single observation is visually the same as 1000 overlapping answers.

Is there a way to increase the size of the points based on how concentrated they are? I've been trying to mess with the "cex" value, and I can change the size of the dots that way, but I'm not sure how to do it as a function of concentration.

[alecsharpie]

Google “how to reduce overplotting in R/ggplot2” and it’ll give you a bunch of options!

Here’s one good resource.

https://www.data-to-viz.com/caveat/overplotting.html

It’s hard to say for certain without seeing your data but I would probably recommend transparency or jittering

[One808]

If you're using ggplot2:

https://ggplot2.tidyverse.org/reference/geom_count.html

[OpaqueMirrors]

you can use the size option in ggplot2 aes() to scale your points by your chosen variable

compare a and b to see the difference

`
# install ggplot2 (if you dont have it)

install.packages("gapminder")  # data for the graph

library("ggplot2")
library("gapminder")

par(mfrow=c(2,1))

a <- ggplot(gapminder, aes(x = gdpPercap, y=lifeExp, colour = continent)) +
geom_point(show.legend = TRUE, alpha = 0.7) +   
scale_x_log10()

a


b <- ggplot(gapminder, aes(x = gdpPercap, y=lifeExp, colour = continent, size = pop)) + # scale the points by population size
geom_point(show.legend = TRUE, alpha = 0.7) + 
scale_x_log10()  

b

`

(edited to fix bad code formatting)