Use the code below to re-define the standardize() function and to create a vector with standardized numbers.

standardize <- function (x) {
  (x - mean(x, na.rm = TRUE)) / sd(x, na.rm = TRUE)
}

standardized_vector <-
  standardize(sample(1:100, 30))

1

Using a for()-loop, loop through each element of the vector, add the number pi, and print the result.

There’s a pre-defined value in R for pi. Just type pi and you’ll receive 3.141593. You need to wrap what the function does within the print() function.

solution 

for (number in standardized_vector) {
  print(number + pi)
}
## [1] 2.03279
## [1] 1.781107
## [1] 2.997574
## [1] 4.339883
## [1] 2.871733
## [1] 3.962358
## [1] 2.242526
## [1] 2.955627
## [1] 1.906948
## [1] 3.878464
## [1] 5.598297
## [1] 4.130147
## [1] 1.697213
## [1] 3.081468
## [1] 3.920411
## [1] 2.284473
## [1] 2.703944
## [1] 3.626781
## [1] 2.116684
## [1] 2.32642
## [1] 4.004306
## [1] 2.494208
## [1] 3.039521
## [1] 4.591566
## [1] 2.200578
## [1] 3.333151
## [1] 2.158631
## [1] 4.759354
## [1] 3.542887
## [1] 3.668728

2

Repeat the previous exercise, but this time the results should be printed all at once in a vector. Use the sapply() function here.

You don’t need the print() function anymore.

solution 

sapply(standardized_vector, function (number) {
  number + pi
}) 
##  [1] 2.032790 1.781107 2.997574 4.339883 2.871733 3.962358 2.242526 2.955627 1.906948 3.878464 5.598297 4.130147 1.697213 3.081468
## [15] 3.920411 2.284473 2.703944 3.626781 2.116684 2.326420 4.004306 2.494208 3.039521 4.591566 2.200578 3.333151 2.158631 4.759354
## [29] 3.542887 3.668728

3

Now, we want to have the same output as a list.

You can either use lapply() or map() from the purrr package.

solution 

library(purrr)

lapply(standardized_vector, function (number) {
  number + pi
}) 
## [[1]]
## [1] 2.03279
## 
## [[2]]
## [1] 1.781107
## 
## [[3]]
## [1] 2.997574
## 
## [[4]]
## [1] 4.339883
## 
## [[5]]
## [1] 2.871733
## 
## [[6]]
## [1] 3.962358
## 
## [[7]]
## [1] 2.242526
## 
## [[8]]
## [1] 2.955627
## 
## [[9]]
## [1] 1.906948
## 
## [[10]]
## [1] 3.878464
## 
## [[11]]
## [1] 5.598297
## 
## [[12]]
## [1] 4.130147
## 
## [[13]]
## [1] 1.697213
## 
## [[14]]
## [1] 3.081468
## 
## [[15]]
## [1] 3.920411
## 
## [[16]]
## [1] 2.284473
## 
## [[17]]
## [1] 2.703944
## 
## [[18]]
## [1] 3.626781
## 
## [[19]]
## [1] 2.116684
## 
## [[20]]
## [1] 2.32642
## 
## [[21]]
## [1] 4.004306
## 
## [[22]]
## [1] 2.494208
## 
## [[23]]
## [1] 3.039521
## 
## [[24]]
## [1] 4.591566
## 
## [[25]]
## [1] 2.200578
## 
## [[26]]
## [1] 3.333151
## 
## [[27]]
## [1] 2.158631
## 
## [[28]]
## [1] 4.759354
## 
## [[29]]
## [1] 3.542887
## 
## [[30]]
## [1] 3.668728
standardized_vector %>% 
  map(~.x + pi)
## [[1]]
## [1] 2.03279
## 
## [[2]]
## [1] 1.781107
## 
## [[3]]
## [1] 2.997574
## 
## [[4]]
## [1] 4.339883
## 
## [[5]]
## [1] 2.871733
## 
## [[6]]
## [1] 3.962358
## 
## [[7]]
## [1] 2.242526
## 
## [[8]]
## [1] 2.955627
## 
## [[9]]
## [1] 1.906948
## 
## [[10]]
## [1] 3.878464
## 
## [[11]]
## [1] 5.598297
## 
## [[12]]
## [1] 4.130147
## 
## [[13]]
## [1] 1.697213
## 
## [[14]]
## [1] 3.081468
## 
## [[15]]
## [1] 3.920411
## 
## [[16]]
## [1] 2.284473
## 
## [[17]]
## [1] 2.703944
## 
## [[18]]
## [1] 3.626781
## 
## [[19]]
## [1] 2.116684
## 
## [[20]]
## [1] 2.32642
## 
## [[21]]
## [1] 4.004306
## 
## [[22]]
## [1] 2.494208
## 
## [[23]]
## [1] 3.039521
## 
## [[24]]
## [1] 4.591566
## 
## [[25]]
## [1] 2.200578
## 
## [[26]]
## [1] 3.333151
## 
## [[27]]
## [1] 2.158631
## 
## [[28]]
## [1] 4.759354
## 
## [[29]]
## [1] 3.542887
## 
## [[30]]
## [1] 3.668728