Tidy evaluation is a bit challenging to get your head around. Even after reading programming with dplyr several times, I still struggle when creating functions from time to time. I made a small summary of the most common actions I perform, so I don’t have to dig in the vignettes and on stackoverflow over and over. Each is accompanied with a minimal example on how to implement it. I thought others might find this useful too, so here it is in a blog post. This list is meant to be a living thing so additions and improvements are most welcome. Please do a PR on this file or send an email.
library(tidyverse)
bare to quosure: quo
bare_to_quo <- function(x, var){
x %>% select(!!var) %>% head(1)
}
bare_to_quo(mtcars, quo(cyl))
## cyl
## Mazda RX4 6
bare to quosure in function: enquo
bare_to_quo_in_func <- function(x, var) {
var_enq <- enquo(var)
x %>% select(!!var_enq) %>% head(1)
}
bare_to_quo_in_func(mtcars, mpg)
## mpg
## Mazda RX4 21
quosure to a name: quo_name
bare_to_name <- function(x, nm) {
nm_name <- quo_name(nm)
x %>% mutate(!!nm_name := 42) %>% head(1) %>%
select(!!nm)
}
bare_to_name(mtcars, quo(this_is_42))
## this_is_42
## 1 42
quosure to text: quo_text
quo_to_text <- function(x, var) {
var_enq <- enquo(var)
glue::glue("The following column was selected: {rlang::quo_text(var_enq)}")
}
quo_to_text(mtcars, cyl)
## The following column was selected: cyl
character to name: sym (edited)
char_to_quo <- function(x, var) {
var_enq <- rlang::sym(var)
x %>% select(!!var_enq) %>% head(1)
}
char_to_quo(mtcars, "vs")
## vs
## Mazda RX4 0
multiple bares to quosure: quos
bare_to_quo_mult <- function(x, ...) {
grouping <- quos(...)
x %>% group_by(!!!grouping) %>% summarise(nr = n())
}
bare_to_quo_mult(mtcars, vs, cyl)
## # A tibble: 5 x 3
## # Groups: vs [?]
## vs cyl nr
## <dbl> <dbl> <int>
## 1 0 4 1
## 2 0 6 3
## 3 0 8 14
## 4 1 4 10
## 5 1 6 4
multiple characters to names: syms (edited)
bare_to_quo_mult_chars <- function(x, ...) {
grouping <- rlang::syms(...)
x %>% group_by(!!!grouping) %>% summarise(nr = n())
}
bare_to_quo_mult_chars(mtcars, list("vs", "cyl"))
## # A tibble: 5 x 3
## # Groups: vs [?]
## vs cyl nr
## <dbl> <dbl> <int>
## 1 0 4 1
## 2 0 6 3
## 3 0 8 14
## 4 1 4 10
## 5 1 6 4
quoting full expression
Although quoting column names is most often used, it is by no means the only option. We can use the above to quote full expressions.
filter_func <- function(x, filter_exp) {
filter_exp_enq <- enquo(filter_exp)
x %>% filter(!!filter_exp_enq)
}
filter_func(mtcars, hp == 93)
## mpg cyl disp hp drat wt qsec vs am gear carb
## 1 22.8 4 108 93 3.85 2.32 18.61 1 1 4 1
quoting full expression in a character: parse_expr
filter_by_char <- function(x, char) {
func_call <- rlang::parse_expr(char)
x %>% filter(!!func_call)
}
filter_by_char(mtcars, "cyl == 6") %>% head(1)
## mpg cyl disp hp drat wt qsec vs am gear carb
## 1 21 6 160 110 3.9 2.62 16.46 0 1 4 4
Edit notes
1) I mistakingly thought that rlang::sym(s) created quosures. However, as pointed out to me by a reader, this creates a name, not a quosure. A name however can also be unquoted. See this github discussion.
just_a_name <- rlang::sym("cyl")
class(just_a_name)
## [1] "name"
mtcars %>% select(!!just_a_name) %>% head(1)
## cyl
## Mazda RX4 6
2) Quoting expressions in a character was added roughly a year after the first apperance of this blog.
3) The quo_text example used to be with ggplot2. However, since v.3.0.0 it supports tidy evaluation. Therefore, the example was changed and now it uses glue.