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

function and its variants:**apply()**

- apply()
- lapply()
- sapply()
- tapply()
**mapply()**

Let us see what each of these functions does.

Looping Function | Operation |
---|---|

| Applies a function over the margins of an array or matrix |

| Apply a function over a list or a vector |

| Same as `lapply()` but with simplified results |

| Apply a function over a ragged array |

| Multivariate version of `lapply()` |

: This function applies a given function over the margins of a given array.`apply()`

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 perform**Example:**`# 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)`

**Output:**[, 1] [, 2] [, 3] [1, ] 1 4 7 [2, ] 2 5 8 [3, ] 3 6 9 [1] 12 15 18 [1] 6 15 24

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():`

lapply(list, function, …)

list = Created list

function = the operation which you want to perform**Example:**`# 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)`

**Output:**[[1]] [1] 0 [[2]] [1] 5.329071e-15

This function is used to simplify the result of`sapply():`

`lapply()`

, if possible. Unlike`lapply()`

, 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 perform**Example:**`# 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)`

**Output:**a b 3 8

A vector is returned since the output had a list with elements of length 1.

: This function is used to apply a function over subset of vectors given by a combination of factors.`tapply()`

tapply(vector, factor, function, …)

vector = Created vector

factor = Created factor

function = the operation which you want to perform**Example:**`# 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)`

**Output:**1 2 3 10 18 17

How does the above code work?

: It’s a multivariate version of`mapply()`

`lapply()`

. 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)`

**Output:**[1] 24

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