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
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)