How to add an external legend to ggpairs()?

纵然是瞬间 提交于 2019-11-28 08:34:27
ManojVenkat

I am working on something similar, this is the approach i would take,

  1. Ensure legends are set to 'TRUE' in the ggpairs function call
  2. Now iterate over the subplots in the plot matrix and remove the legends for each of them and just retain one of them since the densities are all plotted on the same column.

    colIdx <- c(3,5,6,7)
    
    for (i in 1:length(colIdx)) {
    
      # Address only the diagonal elements
      # Get plot out of matrix
      inner <- getPlot(p, i, i);
    
      # Add any ggplot2 settings you want (blank grid here)
      inner <- inner + theme(panel.grid = element_blank()) +
        theme(axis.text.x = element_blank())
    
      # Put it back into the matrix
      p <- putPlot(p, inner, i, i)
    
      for (j in 1:length(colIdx)){
        if((i==1 & j==1)){
    
          # Move legend right
          inner <- getPlot(p, i, j)
          inner <- inner + theme(legend.position=c(length(colIdx)-0.25,0.50)) 
          p <- putPlot(p, inner, i, j)
        }
        else{
    
          # Delete legend
          inner <- getPlot(p, i, j)
          inner <- inner + theme(legend.position="none")
          p <- putPlot(p, inner, i, j)
        }
      }
    }
    

Hopefully, someone will show how this can be done with ggpairs(...). I'd like to see that myself. Until then, here is a solution that does not use ggpairs(...), but rather plain vanilla ggplot with facets.

library(ggplot2)
library(reshape2)   # for melt(...)
library(plyr)       # for .(...)
library(data.table)

xx <- with(df, data.table(id=1:nrow(df), group=Region, df[,c(3,5,6,7)]))
yy <- melt(xx,id=1:2, variable.name="H", value.name="xval")
setkey(yy,id,group)
ww <- yy[,list(V=H,yval=xval),key="id,group"]
zz <- yy[ww,allow.cartesian=T]
setkey(zz,H,V,group)
zz <- zz[,list(id, group, xval, yval, min.x=min(xval),min.y=min(yval),
               range.x=diff(range(xval)),range.y=diff(range(yval))),by="H,V"]
d  <- zz[H==V,list(x=density(xval)$x,
                   y=min.y+range.y*density(xval)$y/max(density(xval)$y)),
         by="H,V,group"]
ggplot(zz)+
  geom_point(subset= .(xtfrm(H)<xtfrm(V)), 
             aes(x=xval, y=yval, color=factor(group)), 
             size=3, alpha=0.5)+
  geom_line(subset= .(H==V), data=d, aes(x=x, y=y, color=factor(group)))+
  facet_grid(V~H, scales="free")+
  scale_color_discrete(name="Region")+
  labs(x="", y="")

The basic idea is to melt(...) your df into the proper format for ggplot (xx), make two copies (yy and ww) and run a cartesian join based on id and group (here, id is just a row number and group is the Region variable), to create zz. We do need to calculate and scale the densities externally (in the data table d). In spite of all that, it still runs faster than ggpairs(...).

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