R 分组ID列表上的分配函数

我有一个带有id、开始日期、结束日期以及收入和成本值的数据框

table <- data.frame(id = c(1, 2, 3),
               start = c("2018-01-01", "2018-02-05", "2018-05-30"),
               end = c("2018-01-31", "2018-03-26", "2018-08-31"),
               income = c(100, 225, 399),
               costs = c(37, 98, 113))

table$start <- as.Date(table$start)
table$end <- as.Date(table$end)

就像这样，其中一些时间段跨越n个月，我想按月汇总收入和成本。对于与跨越两个月、三个月或更多个月的期间相关的金额，我希望在两个月、三个月或n个月之间线性分配

问题是，我还想保留id，并对两个变量执行操作（不像前面所问的问题那样是一个变量），这会使整个事情复杂化

我希望得到的是下表：

  id   date      income      costs
  1   2018-01    100         37
  2   2018-02    108         47.04
  2   2018-03    117         50.96
  3   2018-05    8.489362    2.404255
  3   2018-06    127.340426  36.063830
  3   2018-07    131.585106  37.265957
  3   2018-08    131.585106  37.265957

我尝试在id创建的数据帧列表上使用rbindlist，并使用以下函数：

explode <- function(start, end, income) {
              dates <- seq(start, end, "day")
              n <- length(dates)
              rowsum(rep(income, n) / n, format(dates, "%Y-%m"))                  
}

  Map(explode, table$start, table$end, table$income)

---

explode我会选择
数据。表
：

library(data.table)

table_aggregated <- setDT(table)[
  , .(id = id, income = income, costs = costs, day_var = seq(start, end, "day")), by = 1:nrow(table)][
    , `:=` (income_day = income / .N, 
            costs_day = costs / .N,
            date = format(day_var, "%Y-%m")), by = id][
              , .(income = sum(income_day),
                  costs = sum(costs_day)), by = .(id, date)]

你的解决方案本可以奏效。简单地说，向
Map
添加一个新参数，并使用
cbind
扩展您的函数，将收入和成本结合起来，然后
rbind
从
Map
生成的列表：

explode <- function(start, end, income, costs) {
  dates <- seq(start, end, "day")
  n <- length(dates)
  cbind.data.frame(
    date = format(start, "%Y-%m"),
    income = rowsum(rep(income, n) / n, format(dates, "%Y-%m")),
    costs = rowsum(rep(costs, n) / n, format(dates, "%Y-%m")) 
  )
}

data_list <- Map(explode, table$start, table$end, table$income, table$costs)
final_df <- do.call(rbind, data_list)

final_df    
#    date     income     costs
# 2018-01 100.000000 37.000000
# 2018-02 108.000000 47.040000
# 2018-03 117.000000 50.960000
# 2018-05   8.489362  2.404255
# 2018-06 127.340426 36.063830
# 2018-07 131.585106 37.265957
# 2018-08 131.585106 37.265957

explode我不明白接下来几个月的收入、成本计算。你如何得到收入=108，以此类推？它将原始价值的比例部分分配给2月份。换句话说，首先你必须计算起止日期之间的每日收入，然后乘以每月的天数。太简单了！我不敢相信我错过了设置数据帧的cbind解决方案。谢谢
   id    date     income     costs
1:  1 2018-01 100.000000 37.000000
2:  2 2018-02 108.000000 47.040000
3:  2 2018-03 117.000000 50.960000
4:  3 2018-05   8.489362  2.404255
5:  3 2018-06 127.340426 36.063830
6:  3 2018-07 131.585106 37.265957
7:  3 2018-08 131.585106 37.265957

explode <- function(start, end, income, costs) {
  dates <- seq(start, end, "day")
  n <- length(dates)
  cbind.data.frame(
    date = format(start, "%Y-%m"),
    income = rowsum(rep(income, n) / n, format(dates, "%Y-%m")),
    costs = rowsum(rep(costs, n) / n, format(dates, "%Y-%m")) 
  )
}

data_list <- Map(explode, table$start, table$end, table$income, table$costs)
final_df <- do.call(rbind, data_list)

final_df    
#    date     income     costs
# 2018-01 100.000000 37.000000
# 2018-02 108.000000 47.040000
# 2018-03 117.000000 50.960000
# 2018-05   8.489362  2.404255
# 2018-06 127.340426 36.063830
# 2018-07 131.585106 37.265957
# 2018-08 131.585106 37.265957