**ProbaPerception**, and kindly contributed to R-bloggers)

The function **apply()** is certainly one of the most useful function. I was scared of it during a while and refused to use it. But it makes the code so much faster to write and so efficient that we can’t afford not using it.** **If you are like me, that you refuse to use apply because it is scary, read the following lines, it will help you. You want to know** how to use apply() in general, **with a** home-made function **or with** several parameters **? Then, go to see the following examples.

The function apply() is known as extremely useful to improve the speed of our code when we want to operate some functions on a matrix or a vector. I use it, but I do not really know how to use it.

**What is it?**

apply() is a R function which enables to make quick operations on matrix, vector or array. The operations can be done on the lines, the columns or even both of them.

**How does it work?**

The pattern is really simple : apply(**variable**, **margin**, **function**).

–**variable** is the variable you want to apply the **function** to.

–**margin** specifies if you want to apply by row (margin = 1), by column (margin = 2), or for each element (margin = 1:2). Margin can be even greater than 2, if we work with variables of dimension greater than two.

–**function** is the function you want to apply to the elements of your variable.

Because I think example is clearer than anything else, here is the most important example to understand the function apply().

Introduction:

#will apply the function mean to all the elements of each row

apply(a, 1, mean)

# [1] 6 7 8 9 10

#will apply the function mean to all the elements of each column

apply(a, 2, mean)

# [1] 3 8 13

#will apply the function mean to all the elements of each column and of each row, ie each element

apply(a, 1:2, mean)

# [,1] [,2] [,3]

# [1,] 1 6 11

# [2,] 2 7 12

# [3,] 3 8 13

# [4,] 4 9 14

# [5,] 5 10 15

We have just worked on the different margins to show the basic possibilities. But as I said we can also work on other variables such as an array of dimension 3:

#apply() for array of other dimension :

a = array(1:8, dim = c(2,2,2))

apply(a, 3, sum)

# , , 1

#

# [,1] [,2]

# [1,] 1 3

# [2,] 2 4

#

# , , 2

#

# [,1] [,2]

# [1,] 5 7

# [2,] 6 8

**Use a home-made function:**

We can also use our own function. For example, we reproduce the function sum (absolutely useless but let’s keep it simple!).

f1 = function(x){

return(sum(x))

}

apply(a, 1, f1)

**Several parameters:**

A function with several parameters. Here is the main reason why I was never using apply(), I did not know how to do when I had several parameters in a function. This is quite simple, we just have to specifiy in the parameter the variable which is constant.

f2 = function(x1,x2){

x1-x2

}

b = 2

#with the second parameter as an option

apply(a,1,f2,**x2=b**)

# [,1] [,2] [,3] [,4] [,5]

# [1,] -1 0 1 2 3

# [2,] 4 5 6 7 8

# [3,] 9 10 11 12 13

# [3,] 22 24 26 28 30

#with the first parameter as an option

apply(a,1,f2,**x1=b**)

# [,1] [,2] [,3] [,4] [,5]

# [1,] 1 0 -1 -2 -3

# [2,] -4 -5 -6 -7 -8

# [3,] -9 -10 -11 -12 -13

I hope these examples will help you. Personally I use the function apply() since I went through these few examples. Of course there are many other details which can be useful, but these first examples deal with the main useful possibilities of apply().

**leave a comment**for the author, please follow the link and comment on their blog:

**ProbaPerception**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...