I have a dataset with lat/long coordinates and a binary class of interest.
# Simulating the dataset df <- tibble(x = rnorm(100), y = rnorm(100), class = rbernoulli(100))
Now, my objective is to visualize how the rate of
class == 1 varies in the 2D space defined by
y. I'm aware of:
# Density of points ggplot(df) + geom_density_2d(aes(x = x, y = y))
But I would need to do the same plot with the percentage of
class == 1. instead of the density of points itself. It would be basically the ratio of density corresponding to
class == 1 by the density corresponding to the whole dataset.
Is there a way to maybe tweak
stat_density_2d() in order to achieve that goal? Or alternatively, is there any method to obtain this plot?