This version: November, 2014. Stefan Milton Bache
The magrittr (to be pronounced with a sophisticated french accent) is a package with two aims: to decrease development time and to improve readability and maintainability of code. Or even shortr: to make your code smokin' (puff puff)!
To archive its humble aims, magrittr (remember the accent) provides a new
“pipe”-like operator, %>%, with which you may pipe a value forward into an
expression or function call; something along the lines of x %>% f, rather
than f(x). This is not an unknown feature
elsewhere; a prime example is the |> operator used extensively in F#
(to say the least) and indeed this – along with Unix pipes – served as a
motivation for developing the magrittr package.
This vignette describes the main features of magrittr and demonstrates some features which has been added since the initial release.
At first encounter, you may wonder whether an operator such as %>% can really
be all that beneficial; but as you may notice, it semantically changes your
code in a way that makes it more intuitive to both read and write.
Consider the following example, in which the mtcars dataset shipped with
R is munged a little.
library(magrittr)
car_data <-
mtcars %>%
subset(hp > 100) %>%
aggregate(. ~ cyl, data = ., FUN = . %>% mean %>% round(2)) %>%
transform(kpl = mpg %>% multiply_by(0.4251)) %>%
print
cyl mpg disp hp drat wt qsec vs am gear carb kpl
1 4 25.90 108.0 111.0 3.94 2.15 17.75 1.00 1.00 4.50 2.00 11.010
2 6 19.74 183.3 122.3 3.59 3.12 17.98 0.57 0.43 3.86 3.43 8.391
3 8 15.10 353.1 209.2 3.23 4.00 16.77 0.00 0.14 3.29 3.50 6.419
We start with a value, here mtcars (a data.frame). Based on this, we
first extract a subset, then we aggregate the information based on the number
of cylinders, and then we transform the dataset by adding a variable
for kilometers per liter as supplement to miles per gallon. Finally we print
the result before assigning it.
Note how the code is arranged in the logical
order of how you think about the task: data->transform->aggregate, which
is also the same order as the code will execute. It's like a recipe – easy to
read, easy to follow!
A horrific alternative would be to write
car_data <-
transform(aggregate(. ~ cyl,
data = subset(mtcars, hp > 100),
FUN = function(x) round(mean(x, 2))),
kpl = mpg*0.4251)
There is a lot more clutter with parentheses, and the mental task of deciphering the code is more challenging—in particular if you did not write it yourself.
Note also how “building” a function on the fly for use in aggregate is very
simple in magrittr: rather than an actual value as left-hand side in
pipeline, just use the placeholder. This is also very useful in R's
*apply family of functions.
Granted: you may make the second example better, perhaps throw in a few temporary variables (which is often avoided to some degree when using magrittr), but one often sees cluttered lines like the ones presented.
And here is another selling point. Suppose I want to quickly want to add another step somewhere in the process. This is very easy in the to do in the pipeline version, but a little more challenging in the “standard” example.
The combined example shows a few neat features of the pipe (which it is not):
subset and transform expressions.%>% may be used in a nested fashion, e.g. it may appear in expressions within
arguments. This is used in the mpg to kpl conversion.'.', as placeholder. This is used in the aggregate expression.aggregate expression.print (which also returns its
argument). Here, LHS %>% print(), or even LHS %>% print(.) would also work..) as LHS will create a unary function. This is
used to define the aggregator function.One feature, which was not utilized above is piping into anonymous functions, or lambdas. This is possible using standard function definitions, e.g.
car_data %>%
(function(x) {
if (nrow(x) > 2)
rbind(head(x, 1), tail(x, 1))
else x
})
However, magrittr also allows a short-hand notation:
car_data %>%
{
if (nrow(.) > 0)
rbind(head(., 1), tail(., 1))
else .
}
cyl mpg disp hp drat wt qsec vs am gear carb kpl
1 4 26 108 111 4 2 18 1 1 4 2 11.053
3 8 15 350 192 3 4 17 0 0 3 4 6.377
Since all right-hand sides are really “body expressions” of unary functions, this is only the natural extension the simple right-hand side expressions. Of course longer and more complex functions can be made using this approach.
In the first example the anonymous function is enclosed in parentheses. Whenever you want to use a function- or call-generating statement as right-hand side, parentheses are used to evaluate the right-hand side before piping takes place.
Another, less useful example is:
1:10 %>% (substitute(f(), list(f = sum)))
[1] 55
magrittr also provides three related pipe operators. These are not as
common as %>% but they become useful in special cases.
The “tee” operator, %T>% works like %>%, except it returns the left-hand
side value, and not the result of the right-hand side operation.
This is useful when a step in a pipeline is used for its side-effect (printing,
plotting, logging, etc.). As an example (where the actual plot is omitted here):
rnorm(200) %>%
matrix(ncol = 2) %T>%
plot %>% # plot usually does not return anything.
colSums
[1] 6.916 -1.605
The “exposition” pipe operator, %$% exposes the names within the left-hand side
object to the right-hand side expression. Essentially, it is a short-hand for
using the with functions (and the same left-hand side objects are accepted).
This operator is handy when functions do not themselves have a data argument, as for
example lm and aggregate do. Here are a few examples as illustration:
iris %>%
subset(Sepal.Length > mean(Sepal.Length)) %$%
cor(Sepal.Length, Sepal.Width)
data.frame(z = rnorm(100)) %$%
ts.plot(z)
Finally, the compound assignment pipe operator %<>% can be used as the first pipe
in a chain. The effect will be that the result of the pipeline is assigned to the
left-hand side object, rather than returning the result as usual. It is essentially
shorthand notation for expressions like foo <- foo %>% bar %>% baz, which
boils down to foo %<>% bar %>% baz. Another example is
iris$Sepal.Length %<>% sqrt
The %<>% can be used whenever expr <- ... makes sense, e.g.
x %<>% foo %>% barx[1:10] %<>% foo %>% barx$baz %<>% foo %>% barIn addition to the %>%-operator, magrittr provides some aliases for other
operators which make operations such as addition or multiplication fit well
into the magrittr-syntax. As an example, consider:
rnorm(1000) %>%
multiply_by(5) %>%
add(5) %>%
{
cat("Mean:", mean(.),
"Variance:", var(.), "\n")
head(.)
}
Mean: 5.04 Variance: 23.25
[1] 10.019 -10.231 -3.341 -4.997 -1.728 8.690
which could be written in more compact form as
rnorm(100) %>% `*`(5) %>% `+`(5) %>%
{
cat("Mean:", mean(.), "Variance:", var(.), "\n")
head(.)
}
To see a list of the aliases, execute e.g. ?multiply_by.
The magrittr package is also available in a development version at the GitHub development page: github.com/smbache/magrittr.