Efficient Processing With Apply() Exercises

The apply() function is an alternative to writing loops, via applying a function to columns, rows, or individual values of an array or matrix.

The structure of the apply() function is:
apply(X, MARGIN, FUN, ...)

The matrix variable used for the exercises is:
dataset1 <- cbind(observationA = 16:8, observationB = c(20:19, 6:12))

Answers to the exercises are available here.

Exercise 1

Using apply(), find the row means of dataset1

Exercise 2

Using apply(), find the column sums of dataset1

Exercise 3

Use apply() to sort the columns of dataset1

Exercise 4

Using apply(), find the product of dataset1 rows

Exercise 5

Required function:
DerivativeFunction <- function(x) { log10(x) + 1 }

Apply “DerivativeFunction” on the rows of dataset1

Exercise 6

Re-script the formula from Exercise 5, in order to define “DerivativeFunction” inside the apply() function

Exercise 7

Round the output of the Exercise 6 formula to 2 places

Exercise 8

Print the columns of dataset1 with the apply() function

Exercise 9

Find the length of the dataset1 columns

Exercise 10

Use apply() to find the range of numbers
within the dataset1 columns

Related exercise sets:

Optimize Data Exploration With Sapply() – Exercises Applying Functions To Lists Exercises Complex Tables – Exercises 3D plotting exercises Multivariate Apply Exercises