R: multiple ggplot2 plot using d*ply

I know variations on this question have been up several times, but couldn't figure out how to apply those solutions to this particular challenge:

I would like to use ggplot inside a d*ply call to plot the data (data frame dat below) broken up by the v3variable and display a numeric variable v2 for the 3 conditions in v1. I want to have the plots in one page (pdf), so thought I could use dlply to contain resulting plots in a list that then could be fed to the multiplot wrapper function for ggplot2 found in 'Cookbook for R' here

# Multiple plot function
#
# ggplot objects can be passed in ..., or to plotlist (as a list of ggplot objects)
# - cols:   Number of columns in layout
# - layout: A matrix specifying the layout. If present, 'cols' is ignored.
#
# If the layout is something like matrix(c(1,2,3,3), nrow=2, byrow=TRUE),
# then plot 1 will go in the upper left, 2 will go in the upper right, and
# 3 will go all the way across the bottom.
#
multiplot <- function(..., plotlist=NULL, file, cols=1, layout=NULL) {
  require(grid)

  # Make a list from the ... arguments and plotlist
  plots <- c(list(...), plotlist)

  numPlots = length(plots)

  # If layout is NULL, then use 'cols' to determine layout
  if (is.null(layout)) {
    # Make the panel
    # ncol: Number of columns of plots
    # nrow: Number of rows needed, calculated from # of cols
    layout <- matrix(seq(1, cols * ceiling(numPlots/cols)),
                    ncol = cols, nrow = ceiling(numPlots/cols))
  }

 if (numPlots==1) {
    print(plots[[1]])

  } else {
    # Set up the page
    grid.newpage()
    pushViewport(viewport(layout = grid.layout(nrow(layout), ncol(layout))))

    # Make each plot, in the correct location
    for (i in 1:numPlots) {
      # Get the i,j matrix positions of the regions that contain this subplot
      matchidx <- as.data.frame(which(layout == i, arr.ind = TRUE))

      print(plots[[i]], vp = viewport(layout.pos.row = matchidx$row,
                                      layout.pos.col = matchidx$col))
    }
  }
}

Here is a toy data frame:

set.seed(999)
dat <- data.frame(
  v1 = rep(c("A","B","C"),25),
  v2 = runif(75,-1,2),
  v3 = sample(c("hippo", "smoke", "meat"), 75, replace=T))

Here is the best I could come up with - it gives the plots separately but doesnt merge them, and gives a strange output in console. Note that any solution not using multiplot() is just as good for me.

require(dplyr)
require(ggplot2)    
p <- dlply(dat, .(v3), function(x){
      ggplot(x,aes(v1, v2)) +
      geom_point()})

multiplot(plotlist=p, cols=2)

Solution 1:

Here's a different way that avoids multiplot() and uses techniques shown here and here:

library(ggplot2)
library(dplyr)

results <- dat %>%
  group_by(v3) %>%
  do(plot = ggplot(., aes(v1, v2)) + geom_point())

pdf('all.pdf')
invisible(lapply(results$plot, print))
dev.off()

R: multiple ggplot2 plot using d*ply

Solution 1:

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