summarise_all with additional parameter that is a vector - r

Question

Say I have a data frame:
df <- data.frame(a = 1:10,
b = 1:10,
c = 1:10)
I'd like to apply several summary functions to each column, so I use dplyr::summarise_all
library(dplyr)
df %>% summarise_all(.funs = c(mean, sum))
# a_fn1 b_fn1 c_fn1 a_fn2 b_fn2 c_fn2
# 1 5.5 5.5 5.5 55 55 55
This works great! Now, say I have a function that takes an extra parameter. For example, this function calculates the number of elements in a column above a threshold. (Note: this is a toy example and not the real function.)
n_above_threshold <- function(x, threshold) sum(x > threshold)
So, the function works like this:
n_above_threshold(1:10, 5)
#[1] 5
I can apply it to all columns like before, but this time passing the additional parameter, like so:
df %>% summarise_all(.funs = c(mean, n_above_threshold), threshold = 5)
# a_fn1 b_fn1 c_fn1 a_fn2 b_fn2 c_fn2
# 1 5.5 5.5 5.5 5 5 5
But, say I have a vector of thresholds where each element corresponds to a column. Say, c(1, 5, 7) for my example above. Of course, I can't simply do this, as it doesn't make any sense:
df %>% summarise_all(.funs = c(mean, n_above_threshold), threshold = c(1, 5, 7))
If I was using base R, I might do this:
> mapply(n_above_threshold, df, c(1, 5, 7))
# a b c
# 9 5 3
Is there a way of getting this result as part of a dplyr piped workflow like I was using for the simpler cases?

Answer 1

dplyr provides a bunch of context-dependent functions. One is cur_column(). You can use it in summarise to look up the threshold for a given column.
library("tidyverse")
df <- data.frame(
a = 1:10,
b = 1:10,
c = 1:10
)
n_above_threshold <- function(x, threshold) sum(x > threshold)
# Pair the parameters with the columns
thresholds <- c(1, 5, 7)
names(thresholds) <- colnames(df)
df %>%
summarise(
across(
everything(),
# Use `cur_column()` to access each column name in turn
list(count = ~ n_above_threshold(.x, thresholds[cur_column()]),
mean = mean)
)
)
#> a_count a_mean b_count b_mean c_count c_mean
#> 1 9 5.5 5 5.5 3 5.5
This returns NA silently if the current column name doesn't have a known threshold. This is something that you might or might not want to happen.
df %>%
# Add extra column to show what happens if we don't know the threshold for a column
mutate(
x = 1:10
) %>%
summarise(
across(
everything(),
# Use `cur_column()` to access each column name in turn
list(count = ~ n_above_threshold(.x, thresholds[cur_column()]),
mean = mean)
)
)
#> a_count a_mean b_count b_mean c_count c_mean x_count x_mean
#> 1 9 5.5 5 5.5 3 5.5 NA 5.5
Created on 2022-03-11 by the reprex package (v2.0.1)