ggplot2: Grouping bars of 3 way interaction stacked bar plot

Question

I try to plot a stacked bar chart+2 way interaction in a panel including the same chart for 4 experiments. However, I could not dodge bars depending on one of the independent variable. Below is my data.

First I read the data by the code below.

a<-read.table(file.choose(), header=T, dec=",")

 Exp. Gest lag Sint12 Rev12 c12 t1pi t2pi t1i t2i IntWeak inc Total 1 1 1 15,88 3,28 22,52 11,76 4,08 2,28 16,76 3,24 20,2 100 1 1 3 0,88 1,2 61,36 11,84 8,4 1,84 2,32 0,8 11,36 100 1 1 8 0,24 0,24 65,2 10,24 9,2 1,84 2,4 0,48 10,16 100 1 2 1 14,96 4 25,28 15,12 1,92 0,68 16,8 1,56 19,68 100 1 2 3 1,2 0,72 79,36 8,64 2,88 0,64 0,64 0,64 5,28 100 1 2 8 0,16 0,16 86,72 5,36 3,2 0,08 0,48 0,64 3,2 100 2 1 1 30,6 2,2 24,48 4,56 1,32 0,4 17,8 1 17,64 100 2 1 3 0,96 1,04 87,2 5,04 2,16 0,16 0,4 0,8 2,24 100 2 1 8 0,88 0,24 91,92 3,28 1,52 0 0,32 0,88 0,96 100 2 2 1 20,16 2,32 16,52 14,24 0,72 0,44 15,96 1,76 27,88 100 2 2 3 1,04 0,64 83,84 5,84 2 0,08 0,72 1,12 4,72 100 2 2 8 0,24 0 91,04 4,16 1,52 0,08 0 0,72 2,24 100 3A 1 1 35,83 3,92 27,42 2,42 2,08 0,25 7,42 3,63 17,04 100,01 3A 1 3 1,58 1 81 4,5 3,33 0,25 0,33 1,08 6,92 99,99 3A 1 8 1 0 86,92 3,17 1,75 0,08 0,42 0,33 6,33 100 3A 2 1 43,46 2,38 21,29 1,88 1,17 0,17 5,46 4,21 20 100,02 3A 2 3 2 0,75 78,67 3,75 3,25 0,17 0,83 0,92 9,67 100,01 3A 2 8 1,33 0,33 83,25 3 2,17 0 0,67 0,83 8,42 100 3B 1 1 35,5 2,54 29,33 3,04 1,88 0,54 7,46 7,46 12,25 100 3B 1 3 1,58 0,67 79,42 4,58 2,83 0,42 0,67 2,75 7,08 100 3B 1 8 0,83 0,17 88,83 3,17 2,83 0,08 0,42 0,5 3,17 100 3B 2 1 32,33 1,75 17,21 4,5 2,21 0,42 13,21 4,96 23,42 100,01 3B 2 3 2,5 0,25 67,58 8,42 4,25 0,5 1 4,58 10,92 100 3B 2 8 1 0,08 76,83 6,25 4,5 0,08 0,33 3 7,92 99,99

Second I transformed it wide to long format with the code below.

b <- reshape(a, 
         varying = c("Sint12", "Rev12", "c12", "t1pi", "t2pi", "t1i", "t2i", "IntWeak", "inc"), 
         v.names = "score",
         timevar = "variable", 
         times = c("Sint12", "Rev12", "c12", "t1pi", "t2pi", "t1i", "t2i", "IntWeak", "inc"), 
         new.row.names = 1:1000,
         direction = "long")

And the data looks like below after transformation:

 Exp. Gest lag Total variable score id 1 1 1 1 100.00 Sint12 15.88 1 2 1 1 3 100.00 Sint12 0.88 2 3 1 1 8 100.00 Sint12 0.24 3 4 1 2 1 100.00 Sint12 14.96 4 5 1 2 3 100.00 Sint12 1.20 5 6 1 2 8 100.00 Sint12 0.16 6 7 2 1 1 100.00 Sint12 30.60 7 8 2 1 3 100.00 Sint12 0.96 8 9 2 1 8 100.00 Sint12 0.88 9 10 2 2 1 100.00 Sint12 20.16 10 11 2 2 3 100.00 Sint12 1.04 11 12 2 2 8 100.00 Sint12 0.24 12 13 3A 1 1 100.01 Sint12 35.83 13 14 3A 1 3 99.99 Sint12 1.58 14 15 3A 1 8 100.00 Sint12 1.00 15 16 3A 2 1 100.02 Sint12 43.46 16 17 3A 2 3 100.01 Sint12 2.00 17 18 3A 2 8 100.00 Sint12 1.33 18 19 3B 1 1 100.00 Sint12 35.50 19 20 3B 1 3 100.00 Sint12 1.58 20 21 3B 1 8 100.00 Sint12 0.83 21 22 3B 2 1 100.01 Sint12 32.33 22 23 3B 2 3 100.00 Sint12 2.50 23 24 3B 2 8 99.99 Sint12 1.00 24

What I want is; 1st. 4 plots (for each experiment), 2. make an interaction plot by Gest and lag. 3rd; fill the stacks with the color of variable.

In order to do it, I used the code below.

ggplot(data=b, aes(x=interaction(Gest,lag),y=score, fill = variable, ))+geom_bar(stat="identity")+facet_wrap(~Exp., ncol=2)

Plot

Now, the plot is ready. However, when I pass position=dodge argument to geom_bar; it does not work. I would like to have a plot where there is no gap between 1.1&2.1; 1.3&2.3 and 1.8&2.8 (X axes labels). Also, I want to specify the gaps between .1-.3 and .8.

Thanks in advance.

Answer 1

What do you mean by "it does not work"? When I added that, I got a plot that correctly dodged the bars.

If you just meant that you want to modify the spacing, you can do that by adding additional (empty) levels to the factor that is plotted along the x. Note that there are a different number of spaces in each of the additional levels:

ggplot(data=b
       , aes(x= factor(interaction(Gest, lag)
                       , levels = c(1.1,2.1," ",1.3,2.3,"  ",1.8,2.8))
             ,y=score, fill = variable)) +
  geom_bar(stat="identity", position = "dodge") +
  facet_wrap(~Exp., ncol=2) +
  scale_x_discrete(drop = FALSE)

You can go a few steps further if you use the cowplot package. Here, the advantage is that you can do the faceting on the lag variable if you make each experimental plot separately. Then, you can stitch them together. Here, I suppressed the individual legends, and added a shared common legend at the bottom.

sepPlots <- lapply(unique(b$Exp.), function(thisExp){
  b %>%
    filter(Exp. == thisExp) %>%
    ggplot(aes(x = as.factor(Gest)
               , y = score
               , fill = variable)) +
    geom_bar(stat="identity", position = "dodge") +
    facet_wrap(~lag, nrow = 1
               , labeller = label_both
               , switch = "x") +
    xlab("Gest") +
    ggtitle(paste("Experiment:", thisExp))

})


expPlots <-
  plot_grid(plotlist = lapply(sepPlots, function(x){x + guides(fill = "none")}))

plot_grid(expPlots
          , get_legend(sepPlots[[1]] + theme(legend.direction   = "horizontal"))
          , nrow = 2
          , rel_heights = c(1, 0.1))