R: saving ggplot2 plots in a list

You can vastly simplify your code by:

1. Using facets, rather than manually arranging multiple plots
2. Melting your data with the function melt in package reshape2
3. This means you can remove the loop

Here is a complete rewrite of your code, with no loop in sight.

data_ <- swissdata_ <- na.omit(data_)u <- c(2, 3, 4, 5, 6)plotData <- data_[,u]bw <- 5plotType <- 'frequency'library(ggplot2)library(reshape2)mdat <- melt(plotData)if(plotType=='probability'){  ph <- ggplot(mdat, aes(value)) +    geom_histogram(aes(y=..density..), binwidth=bw, colour='black', fill='skyblue') +     geom_density() +     facet_wrap(~variable, scales="free")} if(plotType=='frequency'){  ph <- ggplot(mdat, aes(value)) +    geom_histogram(aes(y=..count..), binwidth=bw, colour='black', fill='skyblue') +     geom_density() +     facet_wrap(~variable, scales="free")}print(ph)

The resulting graphics:

Probability:

Frequency

Instead of mapping aesthetics using aes, you might be better off using aes_string:

 for(i in 1:length(u)) {   probabilityHistogram <- ggplot(plotData, aes_string(x=names(plotData)[i]))   histogramList[[i]] <-  probabilityHistogram + geom_histogram(aes(y=..density..),     binwidth=bw, colour='black', fill='skyblue') + geom_density() + scale_x_continuous(names(plotData)[i]) + opts(legend.position='none') }

That worked for me, at least. This avoids having to subset your data and allows you to reference the column you want to plot by quoted name.