Loop over string variables in R

When programming in Stata I often find myself using the loop index in the programming. For example, I'll loop over a list of the variables nominalprice and realprice:

local list = "nominalprice realprice"
foreach i of local list {
  summarize `i'
  twoway (scatter `i' time)
  graph export "C:\TimePlot-`i'.png"
}

This will plot the time series of nominal and real prices and export one graph called TimePlot-nominalprice.png and another called TimePlot-realprice.png.

In R the method I've come up with to do the same thing would开发者_Python百科 be:

clist <- c("nominalprice", "realprice")
for (i in clist) {
  e <- paste("png(\"c:/TimePlot-",i,".png\")", sep="")
  eval(parse(text=e))
  plot(time, eval(parse(text=i)))
  dev.off() 
}

This R code looks unintuitive and messy to me and I haven't found a good way to do this sort of thing in R yet. Maybe I'm just not thinking about the problem the right way? Can you suggest a better way to loop using strings?

---

As other people have intimated, this would be easier if you had a dataframe with columns named nominalprice and realprice. If you do not, you could always use get. You shouldn't need parse at all here.

clist <- c("nominalprice", "realprice")
for (i in clist) {
   png(paste("c:/TimePlot-",i,".png"), sep="")
   plot(time, get(i))
   dev.off() 
}

---

If your main issue is the need to type eval(parse(text=i)) instead of ``i'`, you could create a simpler-to-use functions for evaluating expressions from strings:

e = function(expr) eval(parse(text=expr))

Then the R example could be simplified to:

clist <- c("nominalprice", "realprice")
for (i in clist) {
  png(paste("c:/TimePlot-", i, ".png", sep=""))
  plot(time, e(i))
  dev.off() 
}

---

Using ggplot2 and reshape:

library(ggplot2)
library(reshape)
df <- data.frame(nominalprice=rexp(10), time=1:10)
df <- transform(df, realprice=nominalprice*runif(10,.9,1.1))
dfm <- melt(df, id.var=c("time"))
qplot(time, value, facets=~variable, data=dfm)

---

I don't see what's especially wrong with your original solution, except that I don't know why you're using the eval() function. That doesn't seem necessary to me.

You can also use an apply function, such as lapply. Here's a working example. I created dummy data as a zoo() time series (this isn't necessary, but since you're working with time series data anyway):

# x <- some time series data
time <- as.Date("2003-02-01") + c(1, 3, 7, 9, 14) - 1
x <- zoo(data.frame(nominalprice=rnorm(5),realprice=rnorm(5)), time)
lapply(c("nominalprice", "realprice"), function(c.name, x) { 
  png(paste("c:/TimePlot-", c.name, ".png", sep=""))
  plot(x[,c.name], main=c.name)
  dev.off()
}, x=x)