17.3 Updating a container object with a loop

Figure 17.3: This is what I got when I googled ``funny container’’.

For many loops, you may want to update values of a ‘container’ object with each iteration of a loop. We can easily do this using indexing and assignment within a loop.

Let’s do an example with the examscores dataframe. We’ll use a loop to calculate how many students failed each of the 4 exams – where failing is a score less than 50. To do this, we will start by creating an NA vector called failure.percent. This will be a container object that we’ll update later with the loop.

# Create a container object of 4 NA values
failure.percent <- rep(NA, 4)

We will then use a loop that fills this object with the percentage of failures for each exam. The loop will go over each column in examscores, calculates the percentage of scores less than 50 for that column, and assigns the result to the ith value of failure.percent. For the loop, our loop object will be i and our loop vector will be 1:4.

for(i in 1:4) { # Loop over columns 1 through 4

  # Get the scores for the ith column
  x <- examscores[,i] 
  
  # Calculate the percent of failures
  failures.i <- mean(x < 50)  
  
   # Assign result to the ith value of failure.percent
  failure.percent[i] <- failures.i 

}

Now let’s look at the result.

failure.percent
## [1] 0.50 1.00 0.03 0.97

It looks like about 50% of the students failed exam 1, everyone (100%) failed exam 2, 3% failed exam 3, and 97% percent failed exam 4. To calculate failure.percent without a loop, we’d do the following:

# Calculate failure percent without a loop
failure.percent <- rep(NA, 4)
failure.percent[1] <- mean(examscores[,1] < 50)
failure.percent[2] <- mean(examscores[,2] < 50)
failure.percent[3] <- mean(examscores[,3] < 50)
failure.percent[4] <- mean(examscores[,4] < 50)
failure.percent
## [1] 0.50 1.00 0.03 0.97

As you can see, the results are identical.