Vectorization

most of R’s functions are vectorized – meaning the function will operate on all elements of a vector without needing to loop throu and act on each element one at a time
this makes writing code more concise, easy to read, and less error prone

x <- 1:4
x * 2

## [1] 2 4 6 8

multiplication above happened to each element of a vector
we can also add two vectors together

y <- 6:9
x + y

## [1]  7  9 11 13

something liek this:

x:  1  2  3  4
    +  +  +  +
y:  6  7  8  9
---------------
    7  9 11 13

Challenge 1

http://swcarpentry.github.io/r-novice-gapminder/09-vectorization#challenge-1

comparison operators, logical operators and functions are vectorized

comparison operators

x > 2

## [1] FALSE FALSE  TRUE  TRUE

** logical operators**

a <- x > 3  # or, for clarity, a <- (x > 3)
a

## [1] FALSE FALSE FALSE  TRUE

TIP: any() will return TRUE if any element of a vector is TRUE all() will return TRUE if all elements of a vector are TRUE
most functions also operate element-wise on vectors

functions

x <- 1:4
log(x)

## [1] 0.0000000 0.6931472 1.0986123 1.3862944

vectorized operatos work element-wise on matrices

m <- matrix(1:12, nrow=3, ncol=4)
m * -1

##      [,1] [,2] [,3] [,4]
## [1,]   -1   -4   -7  -10
## [2,]   -2   -5   -8  -11
## [3,]   -3   -6   -9  -12

Challenge #3

http://swcarpentry.github.io/r-novice-gapminder/09-vectorization/