Sum rows in R and store the new value in a new dataframe - r

Question

I have a dataframe that looks like this:
Year
Month
total_volume
us_assigned
1953
October
55154
18384.667
1953
November
22783
7594.333
1953
December
20996
6998.667
1954
January
22096
7365.333
1954
February
18869
6289.667
1954
March
11598
3866.000
1954
April
37051
12350.333
1954
May
105856
35285.333
1954
June
61320
20440.000
1954
July
44084
14694.667
1954
August
175152
58384.000
1954
September
80071
26690.333
The dataframe goes to the year 2021 with monthly observations as shown in the table above. I am trying to sum up 12 months (i.e., rows) at a time (from Oct. to Sept.) for the column "us_assigned" and save this value in a new dataframe, which would look like this:
Year
us_assigned
1
218343
2
3
Year 2 would have the sum of the next 12 months (i.e., the next Oct.-Sept.) and so on and so forth. I have thought of simply summing the rows by specifying them, like below, but this seems too tedious.
sum(us_volume[1:12,4])
I am sure there is a much easier way to do this. I am not too proficient with R so I appreciate any help.

Answer 1

This is relatively straightforward using group_by() and summarise() from the dplyr package, e.g.
library(dplyr)
df <- read.table(text = "Year Month total_volume us_assigned
1953 October 55154 18384.667
1953 November 22783 7594.333
1953 December 20996 6998.667
1954 January 22096 7365.333
1954 February 18869 6289.667
1954 March 11598 3866.000
1954 April 37051 12350.333
1954 May 105856 35285.333
1954 June 61320 20440.000
1954 July 44084 14694.667
1954 August 175152 58384.000
1954 September 80071 26690.333", header = TRUE)
df2 <- df %>%
mutate(Year_int = cumsum(Month == "October")) %>% # every Oct add 1 to Year_int
group_by(Year_int) %>%
summarise(us_assigned = sum(us_assigned))
df2
#> # A tibble: 1 × 2
#> Year_int us_assigned
#> <int> <dbl>
#> 1 1 218343.
Created on 2023-01-23 with reprex v2.0.2