R: saving ggplot2 plots in a list

Question

I am writing a R code that allows users to select columns from a data and plots histograms for each of them. Hence, I am using a 'for' loop to generate the required number of plots using the ggplot2 library and save them in a single list. But the problem I am facing is that, at every iteration of the 'for' loop, all objects in the list are storing the same plot. Thus, the final output consists of a grid of histograms, labeled differently but depicting the same(last) column. I understand that this question is quite old and I found the answers on renaming ggplot2 graphs in a for loop and https://stat.ethz.ch/pipermail/r-help/2008-February/154438.html to be a useful starting point. I have used the standard Swiss Fertility dataset available in R to generate the plots. Here is the code:- ``` data_ <- swiss data_ <- na.omit(data_) u <- c(2, 3, 4, 5, 6) plotData <- data_[,u] bw <- 5 plotType <- 'probability' library(ggplot2) library(gridExtra) histogramList <- vector('list', length(u)) if(pl…

Accepted Answer

You can vastly simplify your code by:

- Using facets, rather than manually arranging multiple plots

- Melting your data with the function `melt` in package `reshape2`

- This means you can remove the loop

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

```
data_ <- swiss
data_ <- na.omit(data_)

u <- c(2, 3, 4, 5, 6)
plotData <- data_[,u]
bw <- 5
plotType <- '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

R: saving ggplot2 plots in a list

Solution

Problem