Categorize numeric variable into group/ bins/ breaks

Question

I am trying to categorize a numeric variable (age) into groups defined by intervals so it will not be continuous. I have this code:

data$agegrp(data$age >= 40 & data$age <= 49) <- 3 data$agegrp(data$age >= 30 & data$age <= 39) <- 2 data$agegrp(data$age >= 20 & data$age <= 29) <- 1 

the above code is not working under survival package. It's giving me:

invalid function in complex assignment 

Can you point me where the error is? data is the dataframe I am using.

Answer 1

I would use findInterval() here:

First, make up some sample data

set.seed(1) ages <- floor(runif(20, min = 20, max = 50)) ages # [1] 27 31 37 47 26 46 48 39 38 21 26 25 40 31 43 34 41 49 31 43 

Use findInterval() to categorize your "ages" vector.

findInterval(ages, c(20, 30, 40)) # [1] 1 2 2 3 1 3 3 2 2 1 1 1 3 2 3 2 3 3 2 3 

Alternatively, as recommended in the comments, cut() is also useful here:

cut(ages, breaks=c(20, 30, 40, 50), right = FALSE) cut(ages, breaks=c(20, 30, 40, 50), right = FALSE, labels = FALSE) 

Answer 2

We can use dplyr:

library(dplyr)  data <- data %>% mutate(agegroup = case_when(age >= 40  & age <= 49 ~ '3',                                              age >= 30  & age <= 39 ~ '2',                                              age >= 20  & age <= 29 ~ '1')) # end function 

Compared to other approaches, dplyr is easier to write and interpret.