Site icon R-bloggers

Efficient Processing With Apply() Exercises

[This article was first published on R-exercises, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

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

To leave a comment for the author, please follow the link and comment on their blog: R-exercises.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.