Storing ggplot objects in a list from within loop in R

In addition to the other excellent answer, here’s a solution that uses “normal”-looking evaluation rather than eval. Since for loops have no separate variable scope (i.e. they are performed in the current environment) we need to use local to wrap the for block; in addition, we need to make i a local variable — which we can do by re-assigning it to its own name¹:

myplots <- vector('list', ncol(data2))

for (i in seq_along(data2)) {
    message(i)
    myplots[[i]] <- local({
        i <- i
        p1 <- ggplot(data2, aes(x = data2[[i]])) +
            geom_histogram(fill = "lightgreen") +
            xlab(colnames(data2)[i])
        print(p1)
    })
}

However, an altogether cleaner way is to forego the for loop entirely and use list functions to build the result. This works in several possible ways. The following is the easiest in my opinion:

plot_data_column = function (data, column) {
    ggplot(data, aes_string(x = column)) +
        geom_histogram(fill = "lightgreen") +
        xlab(column)
}

myplots <- lapply(colnames(data2), plot_data_column, data = data2)

This has several advantages: it’s simpler, and it won’t clutter the environment (with the loop variable i).

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¹ This might seem confusing: why does i <- i have any effect at all? — Because by performing the assignment we create a new, local variable with the same name as the variable in the outer scope. We could equally have used a different name, e.g. local_i <- i.

Because of all the quoting of expressions that get passed around, the i that is evaluated at the end of the loop is whatever i happens to be at that time, which is its final value. You can get around this by eval(substitute(ing in the right value during each iteration.

myplots <- list()  # new empty list
for (i in 1:4) {
    p1 <- eval(substitute(
        ggplot(data=data.frame(data2),aes(x=data2[ ,i]))+ 
          geom_histogram(fill="lightgreen") +
          xlab(colnames(data2)[ i])
    ,list(i = i)))
    print(i)
    print(p1)
    myplots[[i]] <- p1  # add each plot into plot list
}
multiplot(plotlist = myplots, cols = 4)

Using lapply works too as x exists within the anonymous function environment (using mtcars as data):

plot <- lapply(seq_len(ncol(mtcars)), FUN = function(x) {
  ggplot(data = mtcars) + 
    geom_line(aes(x = mpg, y = mtcars[ , x]), size = 1.4, color = "midnightblue", inherit.aes = FALSE) +
    labs(x="Date", y="Value", title = "Revisions 1M", subtitle = colnames(mtcars)[x]) +
    theme_wsj() +
    scale_colour_wsj("colors6")
})