Saving ggplot object [duplicate] - r

Question

I'm using a for loop to assign ggplots to a list, which is then passed to plot_grid() (package cowplot). plot_grid places multiple ggplots side by side in a single figure. This works fine manually, but when I use a for loop, the last plot generated is repeated in each subframe of the figure (shown below). In other words, all the subframes show the same ggplot.
Here is a toy example:
require(cowplot)
dfrm <- data.frame(A=1:10, B=10:1)
v <- c("A","B")
dfmsize <- nrow(dfrm)
myplots <- vector("list",2)
count = 1
for(i in v){
myplots[[count]] <- ggplot(dfrm, aes(x=1:dfmsize, y=dfrm[,i])) + geom_point() + labs(y=i)
count = count +1
}
plot_grid(plotlist=myplots)
Expected Figure:
Figure from for loop:
I tried converting the list elements to grobs, as described in this question, like this:
mygrobs <- lapply(myplots, ggplotGrob)
plot_grid(plotlist=mygrobs)
But I got the same result.
I think the problem lies in the loop assignment, not plot_grid(), but I can't see what I'm doing wrong.

Answer 1

The answers so far are very close, but unsatisfactory in my opinion. The problem is the following - after your for loop:
myplots[[1]]$mapping
#* x -> 1:dfmsize
#* y -> dfrm[, i]
myplots[[1]]$plot_env
#<environment: R_GlobalEnv>
myplots[[2]]$mapping
#* x -> 1:dfmsize
#* y -> dfrm[, i]
myplots[[2]]$plot_env
#<environment: R_GlobalEnv>
i
#[1] "B"
As the other answers mention, ggplot doesn't actually evaluate those expressions until plotting, and since these are all in the global environment, and the value of i is "B", you get the undesirable results.
There are several ways of avoiding this issue, the simplest of which in fact simplifies your expressions:
myplots = lapply(v, function(col)
ggplot(dfrm, aes(x=1:dfmsize, y=dfrm[,col])) + geom_point() + labs(y=col))
The reason this works, is because the environment is different for each of the values in the lapply loop:
myplots[[1]]$mapping
#* x -> 1:dfmsize
#* y -> dfrm[, col]
myplots[[1]]$plot_env
#<environment: 0x000000000bc27b58>
myplots[[2]]$mapping
#* x -> 1:dfmsize
#* y -> dfrm[, col]
myplots[[2]]$plot_env
#<environment: 0x000000000af2ef40>
eval(quote(dfrm[, col]), env = myplots[[1]]$plot_env)
#[1] 1 2 3 4 5 6 7 8 9 10
eval(quote(dfrm[, col]), env = myplots[[2]]$plot_env)
#[1] 10 9 8 7 6 5 4 3 2 1
So even though the expressions are the same, the results are different.
And in case you're wondering what exactly is stored/copied to the environment of lapply - unsurprisingly it's just the column name:
ls(myplots[[1]]$plot_env)
#[1] "col"

Answer 2

I believe the problem here is that the non-standard evaluation of the aes method delays evaluating i until the plot is actually plotted. By the time of plotting, i is the last value (in the toy example "B") and thus the y aesthetic mapping for all plots refers to that last value. Meanwhile, the labs call uses standard evaluation and so the labels correctly refer to each iteration of i in the loop.
This can be fixed by simply using the standard evaluation version of the mapping function, aes_q:
require(cowplot)
dfrm <- data.frame(A=1:10, B=10:1)
v <- c("A","B")
dfmsize <- nrow(dfrm)
myplots <- vector("list",2)
count = 1
for(i in v){
myplots[[count]] <- ggplot(dfrm, aes_q(x=1:dfmsize, y=dfrm[,i])) + geom_point() + labs(y=i)
count = count +1
}
plot_grid(plotlist=myplots)

Answer 3

There is a nice explanation of what happens with ggplot2's lazy evaluation and for loops in [this answer](https://stackoverflow.com/a/26246791/2461552.
I usually switch to aes_string or aes_ for situations like this so I can use variables as strings in ggplot2.
I find lapply loops easier than a for loop in your case as initializing the list and using the counter can be avoided.
First, I add the x variable to the dataset.
dfrm$index = 1:nrow(dfrm)
Now, the lapply loop, looping through the columns in v.
myplots = lapply(v, function(x) {
ggplot(dfrm, aes_string(x = "index", y = x)) +
geom_point() +
labs(y = x)
})
plot_grid(plotlist = myplots)

Answer 4

I think ggplot is getting confused by looking for your x and y variables inside of dfrm even though you are actually defining them on the fly. If you change the for loop slightly to build a new sub data.frame as the first line it works just fine.
myplots <- list()
count = 1
for(i in v){
df <- data.frame(x = 1:dfmsize, y = dfrm[,i])
myplots[[count]] <- ggplot(df, aes(x=x, y=y)) + geom_point() + labs(y=i)
count = count + 1
}
plot_grid(plotlist=myplots)