lapply() as an alternative to a multiply-nested loop

Avoiding a loop.R

# Alternative to a doubly-nested loop
# Imagine I want to perform an operation on a data frame
# once for each combination of two variables, such as Country and Year
# I can do this with a nested loop, or I can do this with (among other
# things) lapply()

# Generate random data:
allCountries <- LETTERS[1:10]
allYears <- 1990:2012

myData <- expand.grid(allCountries, allYears)  # This is a useful function
colnames(myData) <- c("Country", "Year")
myData$variable1 <- rnorm(nrow(myData))
myData$variable2 <- rnorm(nrow(myData))

head(myData)

# Silly function to perform
myFunction <- function(x, y){
  x * y - x / y
  }

### Doubly-nested loop ###

myData$computedFigure <- NA  # Make an "empty" variable in my data.frame

for(ii in allCountries){
  for(jj in allYears){
    tempX <- myData[myData$Country == ii & myData$Year == jj, c("variable1")]
    tempY <- myData[myData$Country == ii & myData$Year == jj, c("variable2")]
    # "Save" results into appropriate location in my data.frame
    myData[myData$Country == ii & myData$Year == jj, c("computedFigure")] <- myFunction(tempX, tempY)
    }
  }

### Simple lapply() approach ###

computedFigureList <- lapply(1:nrow(myData), function(x){
  tempX <- myData[x, c("variable1")]
  tempY <- myData[x, c("variable2")]
  # "Save" results into appropriate location in my data.frame
  myFunction(tempX, tempY)
  })

# This produces a list. Use unlist() here, to convert to a vector
# and add that vector to the data.frame
myData$computedFigure2 <- unlist(computedFigureList)

with(myData, plot(computedFigure, computedFigure2))