I would like to create age groupings variable from single year ages.
I would like
Under 16, 17-24, 25-34 etc
My dataset is called Pop_2023 and the variable is just called age.
Thanks,
John
Take care with age boundaries. For example, "Under 16" and "17-24" would leave 16 year olds without a category.
Here's a method:
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
Pop_2023 <- data.frame(person = letters,
age = sample(10:40, 26, replace = TRUE))
Pop_2023 |>
mutate(age_group = case_when(age < 16 ~ "Under 16",
age < 25 ~ "16-24",
age < 35 ~ "25-34",
TRUE ~ "35+"))
#> person age age_group
#> 1 a 22 16-24
#> 2 b 16 16-24
#> 3 c 21 16-24
#> 4 d 30 25-34
#> 5 e 29 25-34
#> 6 f 40 35+
#> 7 g 13 Under 16
#> 8 h 22 16-24
#> 9 i 17 16-24
#> 10 j 34 25-34
#> 11 k 34 25-34
#> 12 l 13 Under 16
#> 13 m 35 35+
#> 14 n 14 Under 16
#> 15 o 34 25-34
#> 16 p 20 16-24
#> 17 q 27 25-34
#> 18 r 18 16-24
#> 19 s 20 16-24
#> 20 t 12 Under 16
#> 21 u 40 35+
#> 22 v 20 16-24
#> 23 w 34 25-34
#> 24 x 10 Under 16
#> 25 y 28 25-34
#> 26 z 31 25-34
Created on 2024-10-22 with reprex v2.1.1
1 Like
That's great thanks but how do I add the new age group variable to the original dataset?
As in keep the data that's already there and add a new age groupings variable at the end of this.
Many thanks again,
Just assign the result to the original object (you essentially overwrite the old value)
Pop_2023 <- Pop_2023 |>
mutate(age_group = case_when(age < 16 ~ "Under 16",
age < 25 ~ "16-24",
age < 35 ~ "25-34",
TRUE ~ "35+"))
1 Like
brilliant many thanks 