This instructional exercise points at presenting the apply( ) work collection. The apply( ) function is the foremost basic of all collection. We are going too learn lapply( ), tapply( ), and sapply( ). The apply collection can be seen as a substitute to the loop.

apply() function

R language has a more efficient to perform iterations with the help of Apply functions.

We use apply() over a matrice.

apply(A, MARGIN, FUN)

A - an array
MARGIN - range between numbers
MARGIN=1 - performed on rows
MARGIN=2 - performed on columns
MARGIN=c(1,2) - performed on rows and columns
FUN - apply function.

n1 <- matrix(C<-(1:10),nrow=5, ncol=6)
n1
m1 <- apply(n1, 2, sum)
m1

Output :

lapply() function

lapply( )- l stands for list. The difference between lapply() and apply() is the output of lapply() is a list and lapply() can be used like data frames and lists.

this function does not need margin.

lapply (A, FUN)

movie <- c("ANTMAN","SUPERMAN","AVENGER","SPIDERMAN")
movies_lower <-lapply(movie, tolower)
str(movies_lower)

Output:

sapply() function

This function return a vector not list.

sapply(A, FUN)

dt <- cars
l_cars <- lapply(dt, min)
s_cars <- sapply(dt, min)
l_cars

Output:

tapply() function

the function computes a measure like mean, median, max, min etc.

tapply(A, INDEX, FUN = NULL)

data(iris)
tapply(iris$Sepal.Width, iris$Species, median)

Output: