When trying to solve this problem I encountered a problem with mutate_each
of dplyr
. I wanted to use it within a function and pass arguments to it. It was successful for funs()
but not for matches()
.
Let me show a simple example where the task is to append some tag the values of some variables.
library(dplyr)
mydf <- data.frame(this_var1 = c("a", "b", "c", "d", "e"),
this_var2 = c("b", "c", "d", "e", "f"),
that_var1 = c("x", "y", "z", "w", "u"))
mymutate1 <- function(data, tag) {
data %>% mutate_each(funs(paste0(., tag)))
}
mymutate1(mydf, "_foo")
this_var1 this_var2 that_var1
1 a_foo b_foo x_foo
2 b_foo c_foo y_foo
3 c_foo d_foo z_foo
4 d_foo e_foo w_foo
5 e_foo f_foo u_foo
This works like a charm. However, if I try to control also for which variables the transformation should be applied it fails.
mymutate2 <- function(data, tag, m) {
data %>% mutate_each(funs(paste0(., tag)), matches(m))
}
mymutate2(mydf, "_foo", "this")
This gives the following error: Error in is.string(match) : object 'm' not found
. Why is tag
found whereas m
not?
The code itself works as intended:
mydf %>% mutate_each(funs(paste0(., "_foo")), matches("this"))
this_var1 this_var2 that_var1
1 a_foo b_foo x
2 b_foo c_foo y
3 c_foo d_foo z
4 d_foo e_foo w
5 e_foo f_foo u
You are going to want to use the Standard Evaluation (SE) version of mutate_each
-- that is, mutate_each_
:
mymutate2 <- function(data, tag, m) {
data %>% mutate_each_(funs(paste0(., tag)), ~matches(m))
}
For additional clarity, the following is equivalent:
mymutate3 <- function(data, tag, m) {
data %>% mutate_each_(~paste0(., tag), ~matches(m))
}
And per the vignette:
"It’s best to use a formula [ ~
as opposed to quote()
or using strings ""
], because a formula captures both the expression to evaluate, and the environment in which it should be a evaluated...Using anything other than a formula will fail because it doesn't know which environment to look in."
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