How to create faceted correlation plot using GGPLOT

Question

I have a data frame created the following way.

library(ggplot2)

x <- data.frame(letters[1:10],abs(rnorm(10)),abs(rnorm(10)),type=\"x\")
y <- data.frame(le         


        

Answer 1

Since your data is not in the appropriate format, some reshaping is necessary before it can be plotted.

Firstly, reshape the data to the long format:

library(reshape2)
allM <- melt(all[-1], id.vars = "type")

Split the values along type and val1 vs. val2:

allList <- split(allM$value, interaction(allM$type, allM$variable))

Create a list of all combinations:

allComb <- unlist(lapply(c(1, 3), 
                  function(x)
                    lapply(c(2 ,4), 
                           function(y) 
                             do.call(cbind, allList[c(x, y)]))), 
           recursive = FALSE)

Create a new dataset:

allNew <- do.call(rbind, 
                  lapply(allComb, function(x) {
                                    tmp <- as.data.frame(x)
                                    tmp <- (within(tmp, {xval <- names(tmp)[1]; 
                                                         yval <- names(tmp)[2]}))
                                    names(tmp)[1:2] <- c("x", "y")
                                    tmp}))

Plot:

library(ggplot2)
p <- ggplot(allNew, aes(x = x, y = y)) + 
       geom_smooth(method = "lm")  + 
       geom_point() +
       facet_grid(yval ~ xval) 
# Calculate correlation for each group
library(plyr)
cors <- ddply(allNew, .(yval, xval), summarise, cor = round(cor(x, y), 2))
p + geom_text(data=cors, aes(label=paste("r=", cor, sep="")), x=0.5, y=0.5)

Answer 2

Some of your code was incorrect. This works for me:

p <- ggplot(all, aes(val1, val2))+ geom_smooth(method = "lm")  + geom_point() +
  facet_grid(~type) 
# Calculate correlation for each group
cors <- ddply(all, .(type), summarise, cor = round(cor(val1, val2), 2))
p + geom_text(data=cors, aes(label=paste("r=", cor, sep="")), x=1, y=-0.25)

Edit: Following OP's comment and edit. The idea is to re-create the data with all four combinations and then facet.

# I consider the type in your previous data to be xx and yy
dat <- data.frame(val1 = c(rep(all$val1[all$type == "x"], 2), 
                           rep(all$val1[all$type == "y"], 2)), 
                  val2 = rep(all$val2, 2), 
                  grp1 = rep(c("x", "x", "y", "y"), each=10), 
                  grp2 = rep(c("x", "y", "x", "y"), each=10))

p <- ggplot(dat, aes(val1, val2)) + geom_point() + geom_smooth(method = "lm") + 
     facet_grid(grp1 ~ grp2)
cors <- ddply(dat, .(grp1, grp2), summarise, cor = round(cor(val1, val2), 2))
p + geom_text(data=cors, aes(label=paste("r=", cor, sep="")), x=1, y=-0.25)

Answer 3

There is an additional package ggpubr available now addressing exactly this issue with the stat_cor() function.

library(tidyverse)
library(ggpubr)
ggplot(all, aes(val1, val2))+ 
  geom_smooth(method = "lm")  + 
  geom_point() +  
  facet_grid(~type) +
  stat_cor()