How to optimize case_when in a function?

问题

I would like to write a function that creates a binning variable based on some raw data. Specifically, I have a dateset with the age values for each respondent and I would like to write a function that classifies that person into an age group, where the age group is a parameter of that function.

This is what I started with:

data <- data.frame(age = 18:100)

foo <- function(data, brackets = list(18:24, 25:34, 35:59)) {
  require(tidyverse)
  tmp <- data %>%
    drop_na(age) %>%
    mutate(age_bracket = case_when(age %in% brackets[[1]] ~ paste(brackets[[1]][1], "to", brackets[[1]][length(brackets[[1]])]),
                                   age %in% brackets[[2]] ~ paste(brackets[[2]][1], "to", brackets[[2]][length(brackets[[2]])]),
                                   age %in% brackets[[3]] ~ paste(brackets[[3]][1], "to", brackets[[3]][length(brackets[[3]])])))
print(tmp)
}

As is obvious, the case_when part is very inflexible as I have to specify ahead of time the number of brackets. It is also quite lengthy. I would like to write some sort of loop that looks at the number of elements in the brackets argument and creates these brackets accordingly. So if I wanted to add a 60:Inf age group, the function should add another age group.

After searching online, I found that some use defused expressions (e.g. quos). I am quite unfamiliar with those, so I struggle to use them for my purpose.

回答1:

I think you are looking for the cut function. The following makes the job:

data <- data.frame(age = 18:100)

data$age_bracket <- cut(data$age, breaks = c(0, 18, 25, 35, 60, Inf))

unique(data$age_bracket)
# [1] (0,18]   (18,25]  (25,35]  (35,60]  (60,Inf]
# Levels: (0,18] (18,25] (25,35] (35,60] (60,Inf]

You can also define labels if you don't link brackets default labels. The advantage of using cut rather than hand-coded solution is that you make usual operations (e.g. ordering) with the output of cut

来源：https://stackoverflow.com/questions/60894989/how-to-optimize-case-when-in-a-function

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function

dplyr

tidyverse

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