Mix color and fill aesthetics in ggplot - r

Question

I wonder if there is the possibility to change the fill main colour according to a categorical variable
Here is a reproducible example
df = data.frame(x = c(rnorm(10, mean = 0),
rnorm(10, mean = 3)),
y = c(rnorm(10, mean = 0),
rnorm(10, mean = 3)),
grp = c(rep('a', times = 10),
rep('b', times = 10)),
val = rep(1:10, times = 2))
ggplot(data = df,
aes(x = x,
y = y)) +
geom_point(pch = 21,
aes(color = grp,
fill = val,
size = val))
Of course it is easy to change the circle colour/shape, according to the variable grp, but I'd like to have the a group in shades of red and the b group in shades of blue.
I also thought about using facets, but don't know if the fill gradient can be changed for the two panels.
Anyone knows if that can be done, without gridExtra?
Thanks!

Answer 1

I think there are two ways to do this. The first is using the alpha aesthetic for your val column. This is a quick and easy way to accomplish your goal but may not be exactly what you want:
ggplot(data = df,
aes(x = x,
y = y)) +
geom_point(pch = 21,
aes(alpha=val,
fill = grp,
size = val)) + theme_minimal()
The second way would be to do something similar to this post: Vary the color gradient on a scatter plot created with ggplot2. I edited the code slightly so its not a range from white to your color of interest but from a lighter color to a darker color. This requires a little bit of work and using the scale_fill_identity function which basically takes a variable that has the colors you want and maps them directly to each point (so it doesn't do any scaling).
This code is:
#Rescale val to [0,1]
df$scaled_val <- rescale(df$val)
low_cols <- c("firebrick1","deepskyblue")
high_cols <- c("darkred","deepskyblue4")
df$col <- ddply(df, .(grp), function(x)
data.frame(col=apply(colorRamp(c(low_cols[as.numeric(x$grp)[1]], high_cols[as.numeric(x$grp)[1]]))(x$scaled_val),
1,function(x)rgb(x[1],x[2],x[3], max=255)))
)$col
df
ggplot(data = df,
aes(x = x,
y = y)) +
geom_point(pch = 21,
aes(
fill = col,
size = val)) + theme_minimal() +scale_fill_identity()

Answer 2

Thanks to this other post I found a way to visualize the fill bar in the legend, even though that wasn't what I meant to do.
Here's the ouptup
And the code
df = data.frame(x = c(rnorm(10, mean = 0),
rnorm(10, mean = 3)),
y = c(rnorm(10, mean = 0),
rnorm(10, mean = 3)),
grp = factor(c(rep('a', times = 10),
rep('b', times = 10)),
levels = c('a', 'b')),
val = rep(1:10, times = 2)) %>%
group_by(grp) %>%
mutate(scaledVal = rescale(val)) %>%
ungroup %>%
mutate(scaledValOffSet = scaledVal + 100*(as.integer(grp) - 1))
scalerange <- range(df$scaledVal)
gradientends <- scalerange + rep(c(0,100,200), each=2)
ggplot(data = df,
aes(x = x,
y = y)) +
geom_point(pch = 21,
aes(fill = scaledValOffSet,
size = val)) +
scale_fill_gradientn(colours = c('white',
'darkred',
'white',
'deepskyblue4'),
values = rescale(gradientends))
Basically one should rescale fill values (e.g. between 0 and 1) and separate them using another order of magnitude, provided by the categorical variable grp.
This is not what I wanted though: the snippet can be improved, of course, to make the whole thing less manual, but still lacks the simple usual discrete fill legend.