Question

I have a big table of data with ~150 columns. I need to make a series of histograms out of about 1/3rd of them. Rather than putting 50 lines of the same plot command in my script, I want to loop over a list telling me which columns to use. Here is a test dataset to illustrate:

d <- data.frame(c(rep("A",5), rep("B",5)),
                sample(c(1:10), 10, replace=TRUE),     
                sample(c(1:10), 10, replace=TRUE),     
                sample(c(1:10), 10, replace=TRUE),     
                sample(c(1:10), 10, replace=TRUE),     
                sample(c(1:10), 10, replace=TRUE))

colnames(d) <- c("col1","col2","col3","col4","col5","col6" )


ggplot(data=d, aes(col2, fill= col1)) + geom_density(alpha = 0.5)

So, rather than writing this a 50 times and replacing the aes() values, I really want to do something more like this…

cols_to_plot <- c("col2","col4","col6")

for (i in length(cols_to_plot)) {
  ggplot(data=d, aes(cols_to_plot[i], fill= col1)) + geom_density(alpha = 0.5)

} 

But of course, this doesn’t work… Is there a way to do this kind of thing?

Thanks!

Answer 1

I think you’d be better off if you melted your data. Try this:

library(reshape2)
d2 <- melt(d, id='col1')
ggplot(d2, aes(value, fill=col1)) + geom_density(alpha=.5) + facet_wrap(~variable)

Or, if you wanted to do what you originally wanted, use aes_string, like:

ggplot(data=d, aes_string(cols_to_plot[i], fill='col1')) + geom_density(alpha = 0.5)