Tidy eval now supports glue strings
So this works great:
my_summarise5 <- function(data, mean_var ) {
data %>%
mutate(
"mean_{{mean_var}}" := mean({{ mean_var }}),
)
}
mtcars %>% my_summarise5(cyl)
But then
my_summarise5 <- function(data, mean_var ) {
data %>%
mutate(
"mean_{{mean_var}}" := mean({{ mean_var }}),
"mean_{{mean_var}}_plusone" := "mean_{{mean_var}}"+1
)
}
mtcars %>% my_summarise5(cyl)
Throws
Error: Problem with `mutate()` input `mean_cyl_plusone`.
x non-numeric argument to binary
Would some 'paste' or 'glue' thing in the "mean_{{mean_var}}_plusone" := "mean_{{mean_var}}"+1 part fix this?
Note this is obviously not a useful case, its a MWE for the syntax. I actually want to define two new columns with different names, one which uses the other ... otherwise I have to repeat and it also gets messy.
I love the tidyverse, but using base R can have a big payoff, by making your code readable and maintainable.
my_summarise5 <- function (data, mean_var) {
mean_name <- paste0("mean_", mean_var)
plus_one_name <- paste0(mean_name, "_plus_one")
data[[mean_name]] <- mean(data[[mean_var]])
data[[plus_one_name]] <- data[[mean_name]] + 1
data
}
Anybody who knows R can understand the above.
tmp <- data.frame(a = 1:5)
my_summarise5(tmp, "a")
## a mean_a mean_a_plus_one
## 1 1 3 4
## 2 2 3 4
## 3 3 3 4
## 4 4 3 4
## 5 5 3 4
If you want to pass a bare symbol as mean_var, then just add this line to the start of the function:
mean_var <- as.character(substitute(mean_var))
This isn't perfect, because it'll break with deeply nested functions. So you could mix a little tidyverse in by doing (something like) mean_var <- enquo(mean_var). But I still would prefer the simple data manipulation to stuff with mutate and across.