How to blend two overlapping graphs with ggplot2 - r

Question

Using ggplot2, how can I blend two graphs? If I graph two sets over data, the second set of data covers up the first set of data. Is there a way to blend both graphs. I already put the alpha value as low as I can. Any lower and I can't see individual points.
demanalyze <- function(infocode, n = 1){
infoname <- filter(infolookup, column_name == infocode)$description
infocolumn <- as.vector(as.matrix(mydata[infocode]))
ggplot(mydata) +
aes(x = infocolumn) +
ggtitle(infoname) +
xlab(infoname) +
ylab("Fraction of votes each canidate recieved") +
xlab(infoname) +
geom_point(aes(y = sanders_vote_fraction, colour = "Bernie Sanders"), size=I(2)) +#, color = alpha("blue",0.02), size=I(1)) +
stat_smooth(aes(y = sanders_vote_fraction), method = "lm", formula = y ~ poly(x, n), size = 1, color = "darkblue", se = F) +
geom_point(aes(y = clinton_vote_fraction, colour = "Hillary Clinton"), size=I(2)) +#, color = alpha("red",0.02), size=I(1)) +
stat_smooth(aes(y = clinton_vote_fraction), method = "lm", formula = y ~ poly(x, n), size = 1, color = "darkred", se = F) +
scale_colour_manual("",
values = c("Bernie Sanders" = alpha("blue",0.005), "Hillary Clinton" = alpha("red",0.005))
) +
guides(colour = guide_legend(override.aes = list(alpha = 1)))
}
By blend, I mean of a there is a red point and a blue point in the same spot, it should show up as purple.

Answer 1

Looking at the plot, my guess is that the issue is a ton of red stacking on top of each other, blocking the blue below. I think you may need to randomize the layering on the graph, which will require generating a single data.frame. Alternatively, if Hillary+Bernie always equals 1, you may be able to just plot that. If they don't, and you don't want to lose too much information, you could plot just one metric of (Hillary)/(Bernie+Hillary).
Example:
geom_point(aes(y = clinton_vote_fraction / ( clinton_vote_fraction + sanders_vote_fraction)
, colour = "Clinton Share"), size=I(2))
And here is an example with the melting approach:
library(dplyr)
library(reshape2)
df <-
data.frame(
metric = rnorm(1000)
, Clinton = rnorm(1000, 48, 10)
) %>%
mutate(Sanders = 100 - Clinton - rnorm(4))
meltDF <-
melt(df, "metric"
, variable.name = "Candidate"
, value.name = "Vote Share")
ggplot(meltDF %>%
arrange(sample(1:nrow(.)))
, aes(x = metric
, y = `Vote Share`
, col = Candidate)) +
geom_point(size = 2, alpha = 0.2) +
geom_smooth(se = FALSE, alpha = 1, show.legend = FALSE) +
scale_colour_manual("",
values = c("Clinton" = "darkblue"
, "Sanders" = "red3")
) +
theme_minimal()