multiple graphs in one canvas using ggplot2

Question

I am trying to merge two ggplot2 plots into one based on this table:

   Type    RatingA  RatingB
1  One     3        36
2  Two     5        53
3  One     5           


        

Answer 1

Julio,

You mention that p1 and p2 have the same x-axis, but the reordering you do based on mean does not make them the same. p1's axis goes "one --> two --> three" while p2's axis goes "two --> one --> three". Is this intentional?

Regardless, ggplot offers a few other solutions to combine these plots into one, namely colour and faceting (which you may have already tried?). The first step to either of these is to melt your data.frame to long format. We will identify the id variable "Type" and melt assumes the rest of the columns are to be melted.

test.m <- melt(test, id.var = "Type")

A quick check of the structure of the new object indicates most everything is in line, except the levels for type are a bit out of whack:

> str(test.m)
'data.frame':   12 obs. of  3 variables:
 $ Type    : Factor w/ 3 levels "One","Three",..: 1 3 1 1 2 2 1 3 1 1 ...
 $ variable: Factor w/ 2 levels "RatingA","RatingB": 1 1 1 1 1 1 2 2 2 2 ...
 $ value   : int  3 5 5 7 4 8 36 53 57 74 ...

So let's rearrage the levels:

test.m$Type <- factor(test.m$Type, c("One", "Three", "Two"), c("One", "Two", "Three"))

Now for the plotting. With colour:

ggplot(test.m, aes(x = Type, y = value, group = variable, colour = variable)) + 
stat_summary(fun.y = "mean", geom = "point") 

or with facets:

ggplot(test.m, aes(x = Type, y = value, group = variable)) + 
stat_summary(fun.y = "mean", geom = "point") +
facet_grid(variable ~ ., scales = "free")

Note I used the scales = "free" argument in the faceting so that each plot has its' own scale. Simply remove that argument if that's not the effect you want.

Answer 2

You can use grid.arrange() in the gridExtra package like this:

grid.arrange(p1, p2)

Answer 3

this is an old question, but I recently found multiplot function, with make his job very well.

The multiplot function is from Cookbook for R:

The function it self is:

# 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))
    }
  }
}

You need just source this function to your script.