Creating New Age group

Question

I have some age(12:54) and related data for them (here year and ASFR). The year starts from 1933 to 1987. The structure of the data is something like ensuing:

year	age	Asfr
1933	12	.00004
1933	13	.00044
1933	14	.00177
1933	15	.00672
1933	16	.01875
1933	17	.03846
1933	18	.06586
1933	19	.08719
...	...	...
1933	49	.00037
1933	50	.00009
1933	51	.00003
1933	52	.00003
1933	53	.00003
1933	54	.00002

Now, I need codes by which I can turn this data into age groups with the following structure:

"15-19" , "20-24", "25-29", "30-34", "35-39" ,"40-44", "45-49"

in which I want 15-19 age group be the sum of 12, 13, 14, 15, 16, 17, 18, 19

20-24 age group be the sum of 20, 21, 22, 23, 24

Finally, the last age group be the sum of 45, 46, 47, 48, 49, 50, 51, 52, 53,54

I would really appreciate it if someone could help me. Thank you so much in advance.

Answer 1

Here's a possible solution:

# Import tidyverse or dplyr
library(tidyverse)

#create the age groups and group by Year and age_groups    
df %>% mutate(age_groups = cut(df$age,
                           breaks=c(12, 20, 25, 30, 35, 40, 45,55),
                           right= F) ) %>% 
  group_by(year, age_groups) %>% 
  summarise(asfr_total = sum(Asfr))

You should see something like this:

   year age_groups asfr_total
  <dbl> <fct>           <dbl>
1  1933 [12,20)          4.32
2  1933 [20,25)          2.33
3  1933 [25,30)          2.68
4  1933 [30,35)          2.89
5  1933 [35,40)          2.23
6  1933 [40,45)          2.85
7  1933 [45,55)          6.05