The injection operator !!
injects a value or
expression inside another expression. In other words, it modifies a
piece of code before R evaluates it.
There are two main cases for injection. You can inject constant values to work around issues of scoping ambiguity, and you can inject defused expressions like symbolised column names.
Where does !!
work?
!!
does not work everywhere, you can only use it within certain
special functions:
Functions taking defused and data-masked arguments.
Technically, this means function arguments defused with
{{
oren
-prefixed operators likeenquo()
,enexpr()
, etc.Inside
inject()
.
All data-masking verbs in the tidyverse support injection operators
out of the box. With base functions, you need to use inject()
to
enable !!
. Using !!
out of context may lead to incorrect
results, see What happens if I use injection operators out of context?.
The examples below are built around the base function with()
.
Since it's not a tidyverse function we will use inject()
to enable
!!
usage.
Injecting values
Data-masking functions like with()
are handy because you can
refer to column names in your computations. This comes at the price
of data mask ambiguity: if you have defined an env-variable of the
same name as a data-variable, you get a name collisions. This
collision is always resolved by giving precedence to the
data-variable (it masks the env-variable):
The injection operator offers one way of solving this. Use it to inject the env-variable inside the data-masked expression:
Note that the .env
pronoun is a simpler way of solving the
ambiguity. See The data mask ambiguity for more about
this.
Injecting expressions
Injection is also useful for modifying parts of a defused expression. In the following example we use the symbolise-and-inject pattern to inject a column name inside a data-masked expression.
Since with()
is a base function, you can't inject
quosures, only naked symbols and calls. This
isn't a problem here because we're injecting the name of a data
frame column. If the environment is important, try injecting a
pre-computed value instead.
When do I need !!
?
With tidyverse APIs, injecting expressions with !!
is no longer a
common pattern. First, the .env
pronoun solves the
ambiguity problem in a more intuitive way:
cyl <- 100
mtcars %>% dplyr::mutate(cyl = cyl * .env$cyl)
Second, the embrace operator {{
makes the
defuse-and-inject pattern easier to
learn and use.
my_mean <- function(data, var) {
data %>% dplyr::summarise(mean({{ var }}))
}
# Equivalent to
my_mean <- function(data, var) {
data %>% dplyr::summarise(mean(!!enquo(var)))
}
!!
is a good tool to learn for advanced applications but our
hope is that it isn't needed for common data analysis cases.