Section 6 Loops in R

In this brief section, we will go over conducting loops in R.

Loops are a tool in R that are useful for situations where we want to do something over and over and over and … over again, where we just change something small each time.

A quick example using the Basque data from the previous section:

basque <- read.csv("basque.csv", stringsAsFactors = T)

Let’s say I wanted to know the GDP for each region for the earliest year they are in the data.

regionsubset <- subset(basque, region == "Andalucia")
regionsubset$gdpcap[regionsubset$year == min(regionsubset$year)]

## [1] 1.688732

## Repeat for a new region
regionsubset <- subset(basque, region == "Aragon")
regionsubset$gdpcap[regionsubset$year == min(regionsubset$year)]

## [1] 2.288775

## Repeat for a new region
regionsubset <- subset(basque, region == "Baleares")
regionsubset$gdpcap[regionsubset$year == min(regionsubset$year)]

## [1] 3.143959

Ughhh can we automate this? we have 17 regions!!!

unique(basque$region)

##  [1] Andalucia              Aragon                 Principado De Asturias
##  [4] Baleares               Canarias               Cantabria             
##  [7] Castilla Y Leon        Castilla-La Mancha     Cataluna              
## [10] Comunidad Valenciana   Extremadura            Galicia               
## [13] Madrid                 Murcia                 Navarra               
## [16] Basque Country         Rioja                 
## 17 Levels: Andalucia Aragon Baleares Basque Country Canarias ... Rioja

Where we will be going by the end of this section:

gdpminyear <- rep(NA, 17) # empty "container" vector
regions <- unique(basque$region) # what we iterate through
names(gdpminyear) <- unique(basque$region) # labels for our output

for(i in 1:17){
  regionsubset <- subset(basque, region == regions[i])
  gdpminyear[i] <- regionsubset$gdpcap[regionsubset$year == 
                                         min(regionsubset$year)]
}
head(gdpminyear) # output

##              Andalucia                 Aragon Principado De Asturias 
##               1.688732               2.288775               2.502928 
##               Baleares               Canarias              Cantabria 
##               3.143959               1.914382               2.559412

We got all of the answers with just one chunk of code!