Tidy evaluation, most common actions

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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)
  ggplot(x, aes_string(rlang::quo_text(var_enq))) + geom_density()
}
plt <- quo_to_text(mtcars, cyl)

Note that tidy evaluation is not yet implemented in ggplot2, but this will be in future versions. This is a workaround for the meantime, when combining dplyr and ggplot2.

character to quosure: sym

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 quosure: syms

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 expressions

Altough 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

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