First, here's a nice way to setup your data for the reprex:
df <- data.frame(
ID = c(1, 2, 3, 4, 5 ,6, 7, 8, 9, 10), # ID of patient
Age = c(22, 55, 90, 7, 14, 100, 72, 85, 91, 43),# Age of patient
Gender = c(1, 2, 2, 2, 1, 1, 2, 1, 1, 2)# Gender, 1 = Male, 2 = Female
)
I think cut could still work for you (I think you want slightly different breaks...).
library(dplyr)
df %>%
mutate(
age_cut = cut(Age, breaks = c(0,30,35,40,Inf))
)
#> ID Age Gender age_cut
#> 1 1 22 1 (0,30]
#> 2 2 55 2 (40,Inf]
#> 3 3 90 2 (40,Inf]
#> 4 4 7 2 (0,30]
#> 5 5 14 1 (0,30]
#> 6 6 100 1 (40,Inf]
#> 7 7 72 2 (40,Inf]
#> 8 8 85 1 (40,Inf]
#> 9 9 91 1 (40,Inf]
#> 10 10 43 2 (40,Inf]
Created on 2018-05-21 by the reprex package (v0.2.0).