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 `x`

and `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?