This stylistic option has several advantages:
1. Reduced requirements of nested parenthesizes
2. Order of functional operations now read from left to right
3. Organizational style of the code may be improved
The library uses a new operator %>% which basically tells R to take the value of that which is to the left and pass it to the right as an argument. Let us see this in action with some text functions.
require('magrittr') # Let's play with some strings str1 = "A scratch? Your arm's off." str2 = "I've had worse." str1 %>% substr(3,9) #Evaluates to "scratch" str1 %>% strsplit('?',fixed=TRUE) #[] # "A scratch" " Your arm's off." # Pipes can be chained as well str1 %>% paste(str2) %>% toupper() #  "A SCRATCH? YOUR ARM'S OFF. I'VE HAD WORSE." # Let's see how pipes might work with drawing random variables # I like to define a function that allows an element by element maximization vmax <- function(x, maximum=0) x %>% cbind(0) %>% apply(1, max) -5:5 %>% vmax #  0 0 0 0 0 0 1 2 3 4 5 # This is identical to defining the function as: vmax <- function(x, maximum=0) apply(cbind(x,0), 1, max) vmax(-5:5) # Notice that the latter formation uses the same number of parenthsize # and be more readable. # However recently I was drawing data for a simulation in which I wanted to # draw Nitem values from the quantiles of the normal distribution, censor the # values at 0 and then randomize their order. Nitem <- 100 ctmean <- 1 ctsd <- .5 draws <- seq(0, 1, length.out = Nitem+2)[-c(1,Nitem+2)] %>% qnorm(ctmean,ctsd) %>% vmax %>% sample(Nitem) # While this looks ugly, let's see how worse it would have been without pipes draws <- sample(vmax(qnorm(seq(0, 1, length.out = Nitem+2)[-c(1,Nitem+2)] ,ctmean,ctsd)),Nitem) # Both functional sequences are ugly though I think I prefer the first which # I can easily read as seq is passed to qnorm passed to vmax passed to sample # A few things to note with the %>% operator. If you want to send the value to # an argument which is not the first or is a named value, use the '.' mydata <- seq(0, 1, length.out = Nitem+2)[-c(1,Nitem+2)] %>% qnorm(ctmean,ctsd) %>% vmax %>% sample(Nitem) %>% data.frame(index = 1:Nitem , theta = .) # Also not that the operator is not as slow as you might think it should be. # Thus: 1 + 8 %>% sqrt # Returns 3.828427 # Rather than (1 + 8) %>% sqrt #  3