Plot over multiple pages

Question

I have the facet_wrap function to make multiple graphs (n=~51) but they all appear on one page. Now after searching, I found out that ggplot2 can't place graphs on multiple pages.

Is there a way to do this? I looked at this question (Multiple graphs over multiple pages using ggplot) and tried out the code, with little success.

Here is my code for my graphs, it produces ~51 graphs on one page, making them very small and hard to see, if I could print this to 1 graph per page in a pdf, that would be great:

ggplot(indbill, aes(x = prey, y = weight), tab) +
geom_polygon(aes(group = load, color = capture), fill = NA, size = 0.75) +
facet_wrap(~ individual) +
theme(axis.ticks.x = element_blank(),
    axis.text.x = element_text(size=rel(0.5)),
    axis.ticks.y = element_blank(),
    axis.text.y = element_blank()) +
xlab("") + ylab("") +
guides(color = guide_legend(ncol=2)) +
coord_radar()

If someone could write up a little code and explain it to me, that would be great.

Answer 1

One option is to just plot, say, six levels of individual at a time using the same code you're using now. You'll just need to iterate it several times, once for each subset of your data. You haven't provided sample data, so here's an example using the Baseball data frame:

library(ggplot2)
library(vcd) # For the Baseball data
data(Baseball)

pdf("baseball.pdf", 7, 5)
for (i in seq(1, length(unique(Baseball$team87)), 6)) {
   print(ggplot(Baseball[Baseball$team87 %in% levels(Baseball$team87)[i:(i+5)], ], 
                  aes(hits86, sal87)) + 
    geom_point() +
    facet_wrap(~ team87) +
    scale_y_continuous(limits=c(0, max(Baseball$sal87, na.rm=TRUE))) +
    scale_x_continuous(limits=c(0, max(Baseball$hits86))) +
    theme_bw())
}
dev.off()

The code above will produce a PDF file with four pages of plots, each with six facets to a page. You can also create four separate PDF files, one for each group of six facets:

for (i in seq(1, length(unique(Baseball$team87)), 6)) {
pdf(paste0("baseball_",i,".pdf"), 7, 5)
  ...ggplot code...
dev.off()
}

Another option, if you need more flexibility, is to create a separate plot for each level (that is, each unique value) of the facetting variable and save all of the individual plots in a list. Then you can lay out any number of the plots on each page. That's probably overkill here, but here's an example where the flexibility comes in handy.

First, let's create all of the plots. We'll use team87 as our facetting column. So we want to make one plot for each level of team87. We'll do this by splitting the data by team87 and making a separate plot for each subset of the data.

In the code below, split splits the data into separate data frames for each level of team87. The lapply wrapper sequentially feeds each data subset into ggplot to create a plot for each team. We save the output in plist, a list of (in this case) 24 plots.

plist = lapply(split(Baseball, Baseball$team87), function(d) {
  ggplot(d, aes(hits86, sal87)) + 
    geom_point() +
    facet_wrap(~ team87) +
    scale_y_continuous(limits=c(0, max(Baseball$sal87, na.rm=TRUE))) +
    scale_x_continuous(limits=c(0, max(Baseball$hits86))) +
    theme_bw() +
    theme(plot.margin=unit(rep(0.4,4),"lines"),
          axis.title=element_blank())
})

Now we'll lay out six plots at time in a PDF file. Below are two options, one with four separate PDF files, each with six plots, the other with a single four-page PDF file. I've also pasted in one of the plots at the bottom. We use grid.arrange to lay out the plots, including using the left and bottom arguments to add axis titles.

library(gridExtra)

# Four separate single-page PDF files, each with six plots
for (i in seq(1, length(plist), 6)) {
  pdf(paste0("baseball_",i,".pdf"), 7, 5)
  grid.arrange(grobs=plist[i:(i+5)], 
               ncol=3, left="Salary 1987", bottom="Hits 1986")
  dev.off()
}

# Four pages of plots in one PDF file
pdf("baseball.pdf", 7, 5)
for (i in seq(1, length(plist), 6)) {
  grid.arrange(grobs=plist[i:(i+5)], 
               ncol=3, left="Salary 1987", bottom="Hits 1986")
}
dev.off()