How to include density coloring in pairwise correlation scatter plot

Question

I have the following code:

library(GGally)
library(nycflights13)
library(tidyverse)

dat <- nycflights13::flights %>% 
       select(dep_time, sched_dep_time, dep_delay,  arr_time, sched_arr_time, arr_delay)  %>% 
       sample_frac(0.01)
dat
ggpairs(dat)

It produces this:

How can I add the density coloring so that it looks like this:

Answer 1

Using ideas from How to reproduce smoothScatter's outlier plotting in ggplot? , R - Smoothing color and adding a legend to a scatterplot, and How to use loess method in GGally::ggpairs using wrap function you can define your own function to pass to ggpairs.

my_fn <- function(data, mapping, ...){
      p <- ggplot(data = data, mapping = mapping) + 
        stat_density2d(aes(fill=..density..), geom="tile", contour = FALSE) +
        scale_fill_gradientn(colours=rainbow(100))
      p
}

ggpairs(dat, lower=list(continuous=my_fn))

EDIT

From comment: How do you add histogram in the diagonal and remove "Corr:" in the correlation value?

You can set the diagonal and upper arguments. So to add the histogram (assuming you mean geom_histogram) you can use diag=list(continuous=wrap("barDiag", binwidth=100)) and to remove the correlation completely use upper=list(continuous="blank"). If you want to actually remove the text *corr:*, you will need to define a new function - please see the function cor_fun at Change colors in ggpairs now that params is deprecated .

So your plot becomes

ggpairs(dat, lower=list(continuous=my_fn),
        diag=list(continuous=wrap("barDiag", binwidth=100)),
        upper=list(continuous=wrap(cor_fun, sz=10, stars=FALSE))
        )

EDIT

From comment: How do you color the diagonal histogram like in OP?

To colour just add the relevant arguments to the barDiag function, in this case fill and colour. So diag would then be

diag=list(continuous=wrap("barDiag", binwidth=100, fill="brown", col="black")) 

(fill gives the main colour, and col gives the colour to outline the bars)