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I have a dataset with 29 columns and 2500 rows resulting from an test. three columns need to be represented on a plot, the fist two are simple X,Y coordinate pairs representing actual X,Y positions on an image used in the test, the third is a response from the participants giving a simple yes or no answer (recorded as 1 and -1 respectively).

Each X,Y coordinate was used name times in the test, and I'm trying to get an overall bias for each point. The values can be found by a simple sum of the Y,N answers. My problem is that I can't plot the "sum" of the answers, only the density of the yes and no separately. I need to show the bias towards yes and no overall for each point, so having two plots or simply plotting the two sets of results on the same plot is on little value.

In the code I'm using the X value is audioDim1a and the Y value is audioDim2. There are 2 DFs used which have been reduced - one to include all the Y answers and the other all the N answers.

this code uses the two N & Y data frames

ggplot() + 
xlim(0, 110) + ylim(0, 150) + 
stat_density_2d(data = test_plot_N, aes(audioDim1a, audioDim2, alpha="density", fill = "density"), geom = "polygon", size = 0.2, contour = T, n = 150, h = 20, bins = 10, colour = "purple") + stat_density_2d(data = test_plot_Y, aes(audioDim1a, audioDim2, alpha="density", fill = "density"), geom = "polygon", size = 0.2, contour = T, n = 150, h = 20, bins = 10, colour = "green") + geom_point(data = test_plot_N, aes(audioDim1a, audioDim2), colour = "blue", size = 1)

If I use a dataset (see below) with the Y and N combined I hoped to get the situation where if the number of Y and N answers was equal the density would result in a 0 plot and thus the contour fill would be clear/white. This does not happen as it seems to simply show a count of responses rather than an arithmetic sum.

ggplot() + 
xlim(0, 110) + ylim(0, 150) + 
stat_density_2d(data = test_plot, aes(audioDim1a, audioDim2, alpha="density", fill = "density"), geom = "polygon", size = 0.2, contour = T, n = 150, h = 20, bins = 10, colour = "purple") + 
geom_point(data = test_plot_N, aes(audioDim1a, audioDim2), colour = "blue", size = 1)

Do I need to supply the data set and the full R code I'm using?

Any help would be really appreciated.

Karolis Koncevičius
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Braham Hughes
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  • To clarity, the Y & N DFs are test_plot_Y and test_plot_N. The full DF is test_plot. – Braham Hughes Apr 28 '18 at 13:52
  • See this [post](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) on how to create a reproducible example such that other's can help you better. – mnm Apr 28 '18 at 13:57
  • OK, hows this... my.data<-data.frame(x=(rep(runif(10),5)),y=(rep(runif(10),5)),z=sample(c(rep(-1,25),rep(1,25)))) ggplot(data = my.data, aes(x = x, y = y, z = z)) + xlim(0, 1) + ylim(0, 1) + geom_contour() + geom_point(data = my.data, aes(x, y), colour = "blue", size = 1) – Braham Hughes Apr 28 '18 at 15:40
  • better dataset... my.data<-data.frame(x=(rep((1:5),5)),y=(rep((1:5),5)),z=sample(c(rep(-1,10),rep(1,40)))) ggplot(data = my.data, aes(x = x, y = y, z = z)) + xlim(-1, 6) + ylim(-01, 6) + stat_density_2d(aes(alpha = "density", fill = "density"), geom = "polygon", size = 0.2, contour = T, n = 300, h = 1.5, bins = 20, colour = "purple") + geom_point(data = my.data, aes(x, y), colour = "blue", size = 1) - i'm hoping to see different contours for the different distributions of yes (1) and no (-1) for z. – Braham Hughes Apr 28 '18 at 16:03

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