R Select 季度月值

从给定的数据帧中，我try 提取quarterly_values，但是当我try 每三个月改变一次值时，它失败了.

mont_dates <- c("201401", "201402", "201403", "201404", "201405", 
"201406", "201407", "201408", "201409", "201410", "201411", "201412")
cat <- c("new", "old", "undefined", "new", "old", "undefined", 
"undefined", "new", "old", "undefined", "new", "old")
mont_vals <- c(221, 433, 878, 455, 998, 797, 77, 3435, 868, 686, 868, 434)
ID <- c(1,2,3,4,5,6,7,8,9,10,11,12)
df <- data.frame(mont_dates, mont_vals, cat, ID)

函数来提取月值并计算季值

 
Monthly_Qrt_vals <- function(df1) {
  df1 %>%
 mutate(mont_dates = ymd(paste0(mont_dates, "01")),
           quarter = paste0(year(mont_dates), " Q", quarter(mont_dates))) %>%
    arrange(mont_dates) %>%
    mutate(quarterly_values = mont_vals[c(1,seq(3, nrow(mont_vals) , by=3)),])
}
result <- df %>% Monthly_Qrt_vals()
View(result)

         cat ID mont_dates mont_vals quarter
1        new  1 2014-01-01       221 2014 Q1
2        old  2 2014-02-01       433 2014 Q1
3  undefined  3 2014-03-01       878 2014 Q1
4        new  4 2014-04-01       455 2014 Q2
5        old  5 2014-05-01       998 2014 Q2
6  undefined  6 2014-06-01       797 2014 Q2
7  undefined  7 2014-07-01        77 2014 Q3
8        new  8 2014-08-01      3435 2014 Q3
9        old  9 2014-09-01       868 2014 Q3
10 undefined 10 2014-10-01       686 2014 Q4
11       new 11 2014-11-01       868 2014 Q4
12       old 12 2014-12-01       434 2014 Q4

Error个

Error in `mutate()`:
ℹ In argument: `quarterly_values = mont_vals[c(1, seq(3, nrow(mont_vals), by = 3)), ]`.
Caused by error in `seq.default()`:
! 'to' must be of length 1

Expected Outcome
quarterly_values should take values of every third month assign to first row of quarters i.e. 2014 Q1, 2014 Q2.

原始数据集是从2014-2023年开始的，有没有替代的解决方案来获得quarterly_values？

         cat ID mont_dates mont_vals quarter  quarterly_values 
1        new  1 2014-01-01       221 2014 Q1   878
2        old  2 2014-02-01       433 2014 Q1   NA
3  undefined  3 2014-03-01       878 2014 Q1   NA
4        new  4 2014-04-01       455 2014 Q2   797
5        old  5 2014-05-01       998 2014 Q2   NA
6  undefined  6 2014-06-01       797 2014 Q2   NA
7  undefined  7 2014-07-01        77 2014 Q3   77
8        new  8 2014-08-01      3435 2014 Q3   NA
9        old  9 2014-09-01       868 2014 Q3   NA
10 undefined 10 2014-10-01       686 2014 Q4   686
11       new 11 2014-11-01       868 2014 Q4   NA
12       old 12 2014-12-01       434 2014 Q4   NA