索引变量时如何在ggplot2中使用lapply

Question

I would like to generate several hundred boxplots of continuous data from a large data frame, stratified by the factor "year". I started by creating a list from the original data frame that contains each dependent variable and the year.

Here is an example data set that looks like mine:

l<-list(data.frame(year=c(rep("2010",10),rep("2011",10),rep("2012",10)),     
var1=sample(1:100,30,replace=T)), 
    data.frame(year=c(rep("2010",10),rep("2011",10),rep("2012",10)), 
var2=sample(100:200,30,replace=T)),
    data.frame(year=c(rep("2010",10),rep("2011",10),rep("2012",10)), 
var3=sample(25:50,30, replace=T)))

The next step was to apply a ggplot2 function over the list. Neither of these functions produce plots:

lapply(l, function (j) ggplot(j, aes(x=year, y=j[,2], fill=year)) +    
 geom_boxplot() + ylab(names(j[2])) )

lapply(l, function (j) ggplot(j, aes(x=year, y=j[[1]][2], fill=year)) +  
 geom_boxplot() + ylab(names(j[2])) )

The same error message is generated from those scripts:

Error: No layers in plot"

In actuality, my data frame is much larger -- 2800 observations and over 250 different variables with unique descriptive names (eg "M2_loss", "SSC"). Each variable is on a different scale, so using facets is not a good solution. What makes this question different from other examples on stackoverflow is that I am trying to index the data rather than explicitly name it. It is important that I capture the unique name of each variable and use it to label the y-axis.

Any ideas on how to proceed?

Answer 1

If you want to have the lapply function actually create output on hte console screen device, it would be a matter of adding a +geom_boxplot call:

 plist <- lapply(l, function (j) print( ggplot(j, aes(x=year, y=j[,2], fill=year))     
  ylab(names(j[2])) +geom_boxplot() ) )

If you wanted to store in a list and then plot later leave out the print call:

 plist <- lapply(l, function (j)  ggplot(j, aes(x=year, y=j[,2], fill=year)) +
                                      ylab(names(j[2])) +geom_boxplot() ) 
# To print ...
plist[[1]]

Answer 2

If I understand what you want, I think you can make things much simpler by using aes_string instead of aes . This allows you to specify the variables of interest as strings rather than as names. Here is a simple example using the well worn iris data set:

lapply( names(iris)[1:4], function(n) ggplot(data = iris, aes_string(y = n, x = "Species")) + geom_boxplot() ) This generates side-by-side boxplots (by species) for each of the four quantitative variables in the iris data set and should be easy to adjust for your data frame.

Answer 3

The issue turned out to be old versions of R (3.2.2) that was confusing Rstudio. Once I deleted the old version, that solved the problem - my original lapply() function (the first example) works fine.