magrittr - Ceci n'est pas un pipe.

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The magrittr package offers a set of operators which promote semantics that will improve your code by

The operators pipe their left-hand side values forward into expressions that appear on the right-hand side, i.e. one can replace f(x) with x %>% f, where %>% is the (main) pipe-operator. When coupling several function calls with the pipe-operator, the benefit will become more apparent. Consider this pseudo example

the_data <-
  read.csv('/path/to/data/file.csv') %>%
  subset(variable_a > x) %>%
  transform(variable_c = variable_a/variable_b) %>%

Four operations are performed to arrive at the desired data set, and they are written in a natural order: the same as the order of execution. Also, no temporary variables are needed. If yet another operation is required, it is straight-forward to add to the sequence of operations wherever it may be needed.


To install the current development version use devtools:


To install the CRAN version:



Basic piping:

The argument placeholder

Re-using the placeholder for attributes

It is straight-forward to use the placeholder several times in a right-hand side expression. However, when the placeholder only appears in a nested expressions magrittr will still apply the first-argument rule. The reason is that in most cases this results more clean code.

x %>% f(y = nrow(.), z = ncol(.)) is equivalent to f(x, y = nrow(x), z = nrow(x))

The behavior can be overruled by enclosing the right-hand side in braces:

x %>% {f(y = nrow(.), z = ncol(.))} is equivalent to f(y = nrow(x), z = nrow(x))

More advanced right-hand sides and lambdas

To define a unary function on the fly in the pipeline, enclose the body of such function in braces, and refer to the argument as ., e.g.

iris %>% 
    n <- sample(1:10, size = 1)
    H <- head(., n)
    T <- tail(., n)
    rbind(H, T)
  } %>%

Building (unary) functions

Any pipeline starting with the . will return a function which can later be used to apply the pipeline to values. Building functions in magrittr is therefore similar to building other values.

f <- . %>% cos %>% sin 
# is equivalent to 
f <- function(.) sin(cos(.)) 

Tee operations

Some right-hand sides are used for their side effect (e.g. plotting, printing to a file, etc) and it may be convenient to be able to subsequently continue the pipeline. The "tee" operator, %T>% can be used for this purpose and works exactly like %>%, except it returns the left-hand side value, rather than the potential result of the right-hand side operation:

rnorm(200) %>%
matrix(ncol = 2) %T>%
plot %>% # plot usually does not return anything.

Pipe with exposition of variables

Many functions accept a data argument, e.g. lm and aggregate, which is very useful in a pipeline where data is first processed and then passed into such a function. There are also functions that do not have a data argument, for which it is useful to expose the variables in the data. This is done with the %$% operator:

iris %>%
  subset(Sepal.Length > mean(Sepal.Length)) %$%
  cor(Sepal.Length, Sepal.Width)

data.frame(z = rnorm(100)) %$%

Compound assignment pipe operations

There is also a pipe operator which can be used as shorthand notation in situations where the left-hand side is being "overwritten":

iris$Sepal.Length <- 
  iris$Sepal.Length %>%

To avoid the repetition of the left-hand side immediately after the assignment operator, use the %<>% operator:

iris$Sepal.Length %<>% sqrt 

This operator works exactly like %>%, except the pipeline assigns the result rather than returning it. It must be the first pipe operator in a longer chain.

Further information

For more detail, see the package vignette