R 循环遍历数据帧的各行以创建累计和

library(tidyverse)
set.seed(1)
start <- mdy("01/01/2022")
end <- start + as.difftime(99, units = "days")
days <- seq(from = start, to = end, by = 1)
days <- sample(days, 100, replace = T)
expiry <- seq(from = start, to = end + 300, by  = 1)
expiry <- sample(expiry, 100, replace = T)
x <- sample(1:10, 100, replace = T)
df <- tibble(days = days, expiry = expiry, value = x)
df <- df %>% filter(days != expiry) %>% arrange(days)
df$expiry[2] = mdy("01-02-2022") 
df
# A tibble: 100 × 3
   days       expiry     value
   <date>     <date>     <int>
 1 2022-01-01 2022-07-23    10
 2 2022-01-01 2022-01-02     3
 3 2022-01-02 2022-10-27     4
 4 2022-01-06 2022-12-22     2
 5 2022-01-07 2022-03-19     5
 6 2022-01-10 2023-01-08     2
 7 2022-01-13 2022-06-23     8
 8 2022-01-13 2022-05-02     5
 9 2022-01-14 2022-08-02     5
10 2022-01-14 2022-03-06     1
# ℹ 90 more rows
# ℹ Use `print(n = ...)` to see more rows

我要创建的是一个dataframe，它包含一年中每个日期的所有值条目的总和，这些值条目的天数&lt；=date和过期&>；=date.我试了下下面的方法.

days <- seq(from = mdy("01/01/2022"), to = mdy("12-31-2022"), by = 1)
s <- rep(0, length(day))
i = 0

for (d in day){
  for (v in df){
    if (v[1] <= d & v[2] >= d){
      s[i] = s[i] + v[3]
    }
  }
  i <- i + 1
}
tb <- tibble(day, s)
# A tibble: 365 × 2
   day            s
   <date>     <dbl>
 1 2022-01-01     0
 2 2022-01-02     0
 3 2022-01-03     0
 4 2022-01-04     0
 5 2022-01-05     0
 6 2022-01-06     0
 7 2022-01-07     0
 8 2022-01-08     0
 9 2022-01-09     0
10 2022-01-10     0
# ℹ 355 more rows
# ℹ Use `print(n = ...)` to see more rows

这里的结果应该是S的前3个条目是10+3=13，10+3+4=17，10+4=14.自2022-01-03&gt；2022-01-02表中的条目2到期.

基于前10行的预期输出应如下所示:

# A tibble: 10 × 2
   x              y
   <date>     <dbl>
 1 2022-01-01    13
 2 2022-01-02    17
 3 2022-01-03    14
 4 2022-01-04    14
 5 2022-01-05    14
 6 2022-01-06    16
 7 2022-01-07    21
 8 2022-01-08    21
 9 2022-01-09    21
10 2022-01-10    23

从本质上讲，我要做的是模仿EXCEL中的Sumifs函数: