Prerequisite: Data Structures in R Programming
One of the biggest issues with the “for” loop is its memory consumption and its slowness in executing a repetitive task. And when it comes to dealing with large data set and iterating over it, for loop is not advised. R provides many alternatives to be applied to vectors for looping operations that are pretty useful when working interactively on a command line. In this article, we deal with apply()
function and its variants:
- apply()
- lapply()
- sapply()
- tapply()
- mapply()
Let us see what each of these functions does.
Looping Function | Operation |
---|---|
apply() |
Applies a function over the margins of an array or matrix |
lapply() |
Apply a function over a list or a vector |
sapply() |
Same as lapply() but with simplified results |
tapply() |
Apply a function over a ragged array |
mapply() |
Multivariate version of lapply() |
apply()
: This function applies a given function over the margins of a given array.
apply(array, margins, function, …)
array = list of elements
margins = dimension of the array along which the function needs to be applied
function = the operation which you want to performExample:
# R program to illustrate
# apply() function
# Creating a matrix
A
=
matrix(
1
:
9
,
3
,
3
)
print
(A)
# Applying apply() over row of matrix
# Here margin 1 is for row
r
=
apply
(A,
1
,
sum
)
print
(r)
# Applying apply() over column of matrix
# Here margin 2 is for column
c
=
apply
(A,
2
,
sum
)
print
(c)
chevron_rightfilter_noneOutput:
[, 1] [, 2] [, 3] [1, ] 1 4 7 [2, ] 2 5 8 [3, ] 3 6 9 [1] 12 15 18 [1] 6 15 24
lapply():
This function is used to apply a function over a list. It always returns a list of the same length as the input list.
lapply(list, function, …)
list = Created list
function = the operation which you want to performExample:
# R program to illustrate
# lapply() function
# Creating a matrix
A
=
matrix(
1
:
9
,
3
,
3
)
# Creating another matrix
B
=
matrix(
10
:
18
,
3
,
3
)
# Creating a list
myList
=
list
(A, B)
# applying lapply()
determinant
=
lapply(myList, det)
print
(determinant)
chevron_rightfilter_noneOutput:
[[1]] [1] 0 [[2]] [1] 5.329071e-15
sapply():
This function is used to simplify the result oflapply()
, if possible. Unlikelapply()
, the result is not always a list. The output varies in the following ways:-- If output is a list containing elements having length 1, then a vector is returned.
- If output is a list where all the elements are vectors of same length(>1), then a matrix is returned.
- If output contains elements which cannot be simplified or elements of different types, a list is returned.
sapply(list, function, …)
list = Created list
function = the operation which you want to performExample:
# R program to illustrate
# sapply() function
# Creating a list
A
=
list
(a
=
1
:
5
, b
=
6
:
10
)
# applying sapply()
means
=
sapply(A, mean)
print
(means)
chevron_rightfilter_noneOutput:
a b 3 8
A vector is returned since the output had a list with elements of length 1.
tapply()
: This function is used to apply a function over subset of vectors given by a combination of factors.
tapply(vector, factor, function, …)
vector = Created vector
factor = Created factor
function = the operation which you want to performExample:
# R program to illustrate
# tapply() function
# Creating a factor
Id
=
c(
1
,
1
,
1
,
1
,
2
,
2
,
2
,
3
,
3
)
# Creating a vector
val
=
c(
1
,
2
,
3
,
4
,
5
,
6
,
7
,
8
,
9
)
# applying tapply()
result
=
tapply(val,
Id
,
sum
)
print
(result)
chevron_rightfilter_noneOutput:
1 2 3 10 18 17
How does the above code work?
mapply()
: It’s a multivariate version oflapply()
. This function can be applied over several list simultaneously.
mapply(function, list1, list2, …)
function = the operation which you want to perform
list1, list2 = Created lists
Example:
# R program to illustrate
# mapply() function
# Creating a list
A
=
list
(c(
1
,
2
,
3
,
4
))
# Creating another list
B
=
list
(c(
2
,
5
,
1
,
6
))
# Applying mapply()
result
=
mapply(
sum
, A, B)
print
(result)
chevron_rightfilter_noneOutput:
[1] 24