Looooooops

Apply

apply() applies a function to each row or column of a matrix.

# matrix 2x10
m <- matrix(c(1:10, 11:20), nrow = 10, ncol = 2)

# this sums rows values:
apply(m, 1, sum)

##  [1] 12 14 16 18 20 22 24 26 28 30

# this sum column values:
apply(m, 2, sum)

## [1]  55 155

lapply() applies a function to each element of a list.

# list where is a and b element
my_list <- list(a = 1:10, b = 2:20)

# calculate mean of each list elements:
lapply(my_list, mean)

## $a
## [1] 5.5
## 
## $b
## [1] 11

sapply() is more user friendly version of lapply and will return a list of matrix where appropriate.

# calculating mean
sapply(my_list, mean)

##    a    b 
##  5.5 11.0

# what type is result?
class(sapply(my_list, mean))

## [1] "numeric"

mapply() is more or less a multivariate version of sapply. It applies a function to all corresponding elements of each argument.

tapply() applies a function to subsets of a vector.

tapply(mtcars$hp, mtcars$cyl, FUN = sum) 

##    4    6    8 
##  909  856 2929

by applies a function to subsets of a data frame

replicate() is an extremely useful function to generate datasets for simulation purposes. The final argument turn the result into a vector or matric if possible.

replicate(10, rnorm(10), simplify = TRUE )

##             [,1]       [,2]       [,3]        [,4]       [,5]       [,6]
##  [1,] -1.4036653 -0.2410946  0.3749349  1.48155532 -0.1027756  0.1266945
##  [2,]  1.7618949 -0.2876565  0.2667836 -0.58081225  0.5947887  0.9335372
##  [3,]  0.5918905  2.2328522  0.1952886  0.56116675  1.0244861  0.4478738
##  [4,]  0.6120719  2.0435606 -0.5423690 -0.01757601  1.7608420  1.3131877
##  [5,] -1.3132832  0.3534599  2.1618018 -0.29148902 -0.7394857 -0.2890967
##  [6,]  0.3423450  0.9266935 -0.8680827  0.98919269  0.6950112 -0.4495551
##  [7,] -0.1034184 -0.8147407  0.8069193 -0.81572324  0.7283151  0.8521975
##  [8,]  0.6088360 -0.9746051  1.7905596 -0.45408937 -0.5467834 -1.3761973
##  [9,]  0.2460124 -0.1346001 -0.3536862 -0.18009448  0.3803184  0.3885687
## [10,]  0.6478928  0.5722962 -0.2944561 -1.26958025  0.8248690 -0.1079098
##              [,7]       [,8]       [,9]      [,10]
##  [1,]  0.44205957  1.4048126  0.8437445  0.8988182
##  [2,]  0.09833495  0.6802951 -1.2639912 -1.6790651
##  [3,]  0.43408102 -0.1379448  0.9864896 -0.5217732
##  [4,] -0.47644506  0.1855462  0.0364129 -0.1049269
##  [5,] -0.02589849  2.0991884 -0.5774630  2.0435193
##  [6,] -1.59299779 -1.2346848 -0.2972403 -0.7864043
##  [7,] -0.95846129  2.0368645 -0.2122265 -1.3576049
##  [8,]  1.72201604 -1.4632958  0.6328692 -0.7297649
##  [9,] -0.91480124  0.9210964 -1.3353671 -0.1029382
## [10,]  0.31595732 -0.9925505 -0.5596720 -1.1850906

Loops

For-loop runs all values in a vector.

for(valuutta in c("euro","dollari","peso")){
  print(valuutta)
}

## [1] "euro"
## [1] "dollari"
## [1] "peso"

Simple for-loop that print ten times “Hello”.

for (i in 1:4){
  print("Hello")
}

## [1] "Hello"
## [1] "Hello"
## [1] "Hello"
## [1] "Hello"

Same loop using while-loop

i = 1
while(i < 4){
  print("Hello")
  i = i + 1
}

## [1] "Hello"
## [1] "Hello"
## [1] "Hello"