R – Display regression equation and R^2 for each scatter plot when using facet_wrap

ggplot2r

I have a data.frame (which I melted using the melt function), from which I produce multiple scatter plots and fit a regression line using the following:

ggplot(dat, aes(id, value)) + geom_point() + geom_smooth(method="lm", se=FALSE) + facet_wrap(variable~var1, scales="free")

I would like to add the regression equation and the R^2 in each of these scatter plots for the relevant regression (i.e. the one produced by geom_smooth in each scatter plot).

var1 above is just the name of one of the id columns of the melted data and I am facing the same question with facet_grid instad of facet_wrap.

Best Answer

I actually solved this, please see below a worked out example where the dependent variable is var1. This was a time series dataset, please ignore the date part if not relevant for your problem.

library(plyr)
library(ggplot2)

rm(dat)
dat <- read.table("data.txt", header = TRUE, sep = ",")
dat <- transform(dat, date = as.POSIXct(strptime(date, "%Y-%m-%dT%H:%M:%OS")))

rm(dat.m)
dat.m <- melt(dat, id = c('ccy','date','var1'))

lm_eqn = function(df){
  m = lm(var1 ~ value, df);
  eq <- substitute(italic(y) == a + b %.% italic(x)*","~~italic(r)^2~"="~r2, 
                   list(a = format(coef(m)[1], digits = 2), 
                        b = format(coef(m)[2], digits = 2), 
                        r2 = format(summary(m)$r.squared, digits = 3)))
  as.character(as.expression(eq));                 
}

mymax = function(df){
  max(df$value)
}

rm(regs)
regs <- ddply(dat.m, .(ccy,variable), lm_eqn)
regs.xpos <- ddply(dat.m, .(variable), function(df) (min(df$value)+max(df$value))/2)
regs.ypos <- ddply(dat.m, .(ccy,variable), function(df) min(df$var1) + 0.05*(max(df$var1)-min(df$var1)))

regs$y <- regs.ypos$V1
regs$x <- regs.xpos$V1

rm(gp)
gp <- ggplot(data=dat.m, aes(value, var1)) + geom_point(size = 1, alpha=0.75) + geom_smooth() + geom_smooth(method="lm", se=FALSE, color="red") + geom_text(data=regs, size=3, color="red", aes(x=x, y=y, label=V1), parse=TRUE) + facet_grid(ccy~variable, scales="free")
ggsave("data.png", gp, scale=1.5, width=11, height=8)

Related Solutions

R – ggplot2 colour geom_point by factor but geom_smooth based on all data

You can do this fairly easily by stepping back from the 'qplot' wrapper function and using the 'ggplot' and geometry functions directly.

ggplot(mtcars, aes(x=wt, y=mpg)) +
    geom_point(aes(colour=factor(cyl))) +
    geom_smooth(method="lm")

demo chart

Step 1: Set your initial 'ggplot' settings. These are the settings that you want to be defaults for the geometry functions.

ggplot(mtcars, aes(x=wt, y=mpg))

In this case, we are using the 'mtcars' data for all geometries with 'wt' assigned to the x-axis and 'mpg' assigned to the y-axis. By specifying these at the beginning, we lessen the risk of messing something up when copy-pasting into the geometry functions.

Step 2: Draw the point geometry, using the factors of 'cyl' to color the points. This is what the original 'qplot' function was doing, but we're specifying it a little more explicitly.

    geom_point(aes(colour=factor(cyl)))

Step 3: Draw the smoothed linear model. This is exactly what the OP wrote before, but now that the aesthetic of coloring is no longer part of the defaults, the model draws as intended.

    geom_smooth(method="lm")

Chain it all together with the + et voila!

For reference: You could just as easily do this by being explicit in each layer, like so:

ggplot() +
    geom_point(data=mtcars, aes(x=wt, y=mpg, colour=factor(cyl))) +
    geom_smooth(data=mtcars, method="lm", aes(x=wt, y=mpg))

R – How to scale density plots (for several variables) in ggplot having melted data

Is this what you had in mind?

enter image description here

There's a built-in variable, ..scaled.. that does this automatically.

set.seed(1)
df<-data.frame(type=rep(c('A','B'),each=100),x=rnorm(200,1,2)/10,y=rnorm(200))
df.m<-melt(df)
ggplot(df.m) + 
  stat_density(aes(x=value, y=..scaled..,color=variable), position="dodge", geom="line")

Best Answer

Related Solutions

R – ggplot2 colour geom_point by factor but geom_smooth based on all data

R – How to scale density plots (for several variables) in ggplot having melted data

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