There's the old standby par(mfrow=c(x, y)) where x is the number of rows you wish to plot and y the numberof columns. It then posts across and then down as you call the plots. par(mfrow = c(2, 2)) corrplot(cor(mat1)) corrplot(cor(mat2)) corrplot(cor(mat3)) corrplot(cor(mat4)) par(mfrow = c(1, 1)) #To clear layout Will...

Okay, I've worked it out. There weren't any p-values greater than that required by sig.level all of them were less than 0.05. As soon as I edited one value to be greater than 0.05 it made it work eg. weird[1,1] <- 0.1 corrplot(weird) works...

r,scatter-plot,ggally,r-corrplot

Short answer: There doesn't seem to be an elegant or easy way to do it, but here's a workaround. I dug into the ggpairs source code (in the GGally package source available from CRAN) to see how the variable labels are actually drawn. The relevant function in ggpairs.R is print.ggpairs....

Like this? par(mfrow = c(2,2)) corrplot(cormatx[1:6,1:6], method="color") corrplot(cormatx[1:6,7:12], method="color") corrplot(cormatx[7:12,1:6], method="color") corrplot(cormatx[7:12,7:12], method="color") ...

r,data-visualization,heatmap,correlation,r-corrplot

You can try the heatmap.2 function from the gplots package which I like for heatmaps and it will give something very similar to the graph you are after (I rounded to second digit for the example below. Use as many digits as you want): Some data manipulation initially: mycor <-...