Use ddply within a function and include variable of interest as an argument

Question

I am relatively new to R, and trying to use ddply & summarise from the plyr package. This post almost, but not quite, answers my question. I could use some additional ex

Answer 1

With the introduction of quosures in the devel version of dplyr (soon to be released 0.6.0), this becomes a bit more easier

library(dplyr)
descriptives_by_groupN <- function(dataset, group, x) {

   group <- enquo(group)
   x <- enquo(x)

  dataset %>%
         group_by(!!group) %>%
         summarise(Mean = mean(!!x),
                SD = sd(!!x),
                Min = min(!!x),
                Max = max(!!x))
}

descriptives_by_groupN(mtcars, cyl, hp)
# A tibble: 3 × 5
#   cyl      Mean       SD   Min   Max
#  <dbl>     <dbl>    <dbl> <dbl> <dbl>
#1     4  82.63636 20.93453    52   113
#2     6 122.28571 24.26049   105   175
#3     8 209.21429 50.97689   150   335

Here, the input arguments are converted to quosures with enquo, and inside the group_by/summarise, unquote the quosures (!! or UQ) to get it evaluated

Answer 2

I just moved a couple things around in the example function you gave and showed how to get more than one column back out. Does this do what you want?

myFunction2 <- function(x, y, col){
z <- ddply(x, y, .fun = function(xx){
                         c(mean = mean(xx[,col],na.rm=TRUE),
                         max = max(xx[,col],na.rm=TRUE) ) })
return(z)
}

myFunction2(mtcars, "cyl", "hp")

Answer 3

(More of a comment than an answer. I had the same level of difficulty as you when using ddply(...,summarise, ...) inside a function.) This is a base solution that worked the way I expected:

descriptives_by_group <- function(dataset, group, x)
  {aggregate(dataset[[x]], dataset[group], function(x)
      c(  mean = mean(x),
          sd   = sd(x),
          min  = min(x),
          max  = max(x)
         ) )
  }

descriptives_by_group(mtcars, 'cyl', 'hp')

Answer 4

Just use as.quoted function. Example below

simple_ddply <- function(dataset_name, variable_name){
    data <- ddply(dataset_name,as.quoted(variable_name), *remaining input)**