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
##
## 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
##
## 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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