Balharbi · June 28, 2020 01:44 · Sep 12, 2012 · Sep 12, 2012
diff --git a/Avoiding a loop.R b/Avoiding a loop.R
@@ -33,7 +33,7 @@ for(ii in allCountries){
     }
   }
 
-### simply lapply() approach ###
+### Simple lapply() approach ###
 
 computedFigureList <- lapply(1:nrow(myData), function(x){
   tempX <- myData[x, c("variable1")]

diff --git a/Avoiding a loop.R b/Avoiding a loop.R
@@ -0,0 +1,49 @@
+# 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$Year == jj, c("computedFigure")] <- myFunction(tempX, tempY)
+    }
+  }
+
+### simply lapply() approach ###
+
+computedFigureList <- lapply(1:nrow(myData), function(x){
+  tempX <- myData[x, c("variable1")]
+  tempY <- myData[x, c("variable2")]
+  # "Save" results into appropriate location in my data.frame
+  myFunction(tempX, tempY)
+  })
+
+# This produces a list. Use unlist() here, to convert to a vector
+# and add that vector to the data.frame
+myData$computedFigure2 <- unlist(computedFigureList)
+
+with(myData, plot(computedFigure, computedFigure2))
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