Using dplyr within a function, non-standard evaluation - r

Question

Trying to get my head around Non-Standard Evaluation as used by dplyr but without success. I'd like a short function that returns summary statistics (N, mean, sd, median, IQR, min, max) for a specified set of variables.
Simplified version of my function...
my_summarise <- function(df = temp,
to.sum = 'eg1',
...){
## Summarise
results <- summarise_(df,
n = ~n(),
mean = mean(~to.sum, na.rm = TRUE))
return(results)
}
And running it with some dummy data...
set.seed(43290)
temp <- cbind(rnorm(n = 100, mean = 2, sd = 4),
rnorm(n = 100, mean = 3, sd = 6)) %>% as.data.frame()
names(temp) <- c('eg1', 'eg2')
mean(temp$eg1)
[1] 1.881721
mean(temp$eg2)
[1] 3.575819
my_summarise(df = temp, to.sum = 'eg1')
n mean
1 100 NA
N is calculated, but the mean is not, can't figure out why.
Ultimately I'd like my function to be more general, along the lines of...
my_summarise <- function(df = temp,
group.by = 'group'
to.sum = c('eg1', 'eg2'),
...){
results <- list()
## Select columns
df <- dplyr::select_(df, .dots = c(group.by, to.sum))
## Summarise overall
results$all <- summarise_each(df,
funs(n = ~n(),
mean = mean(~to.sum, na.rm = TRUE)))
## Summarise by specified group
results$by.group <- group_by_(df, ~to.group) %>%
summarise_each(df,
funs(n = ~n(),
mean = mean(~to.sum, na.rm = TRUE)))
return(results)
}
...but before I move onto this more complex version (which I was using this example for guidance) I need to get the evaluation working in the simple version first as thats the stumbling block, the call to dplyr::select() works ok.
Appreciate any advice as to where I'm going wrong.
Thanks in advance

Answer 1

The basic idea is that you have to actually build the appropriate call yourself, most easily done with the lazyeval package.
In this case you want to programmatically create a call that looks like ~mean(eg1, na.rm = TRUE). This is how:
my_summarise <- function(df = temp,
to.sum = 'eg1',
...){
## Summarise
results <- summarise_(df,
n = ~n(),
mean = lazyeval::interp(~mean(x, na.rm = TRUE),
x = as.name(to.sum)))
return(results)
}
Here is what I do when I struggle to get things working:
Remember that, just like the ~n() you already have, the call will have to start with a ~.
Write the correct call with the actual variable and see if it works (~mean(eg1, na.rm = TRUE)).
Use lazyeval::interp to recreate that call, and check this by running only the interp to visually see what it is doing.
In this case I would probably often write interp(~mean(x, na.rm = TRUE), x = to.sum). But running that will give us ~mean("eg1", na.rm = TRUE) which is treating eg1 as a character instead of a variable name. So we use as.name, as is taught to us in vignette("nse").