How to define a function in dplyr?

Question

I created a simple pivot table in the dplyr package in R. Here is my working example:

library(dplyr)
mean_mpg <- mean(mtcars$mpg)

# creating         


        

Answer 1

If you have the most recent rlang library update v0.4.0 (June 2019), you can use double curly brackets {{ }} (aka "curly curly") to make programming with dplyr easier.

# Note: needs installation of rlang 0.4.0 or later
get_pivot <- function(data, predictor,target) {
  result <-
    data %>%
    group_by(as.factor( {{ predictor }} )) %>%
    summarise(sum=sum( {{ target }} ),total=n()) %>%
    mutate(percentage=sum*100/total);

  print(result)
}

# Edit -- thank you Rui Barradas
> get_pivot(mtcars, cyl, mpg_cat)
# A tibble: 3 x 4
  `as.factor(cyl)`   sum total percentage
  <fct>            <dbl> <int>      <dbl>
1 4                   11    11      100  
2 6                    3     7       42.9
3 8                    0    14        0  

The reason this is required is that dplyr and other tidyverse packages use "non-standard evaluation" like you encounter with some base R functions, like lm(mpg~factor(am),data=mtcars). This practice often makes "interactive" code shorter, simpler, and easier to read, but at the cost of making programming more complicated. In this case, the {{ }} operator serves to transport the column you specify into the context of the function.

https://www.tidyverse.org/articles/2019/06/rlang-0-4-0/