汇总日期范围重叠的行的列值

时间:2019-08-22 03:16:34

标签: r aggregate overlap date-range

我有一个看起来像这样的数据框:

person    date1       date2     total amount  overlap
  A     2019-03-01  2019-03-16       50               
  A     2019-03-10  2019-03-31      100               
  A     2019-03-20  2019-03-31       70               
  B     2019-03-01  2019-03-12      200               
  B     2019-03-01  2019-03-20      130               
  B     2019-03-16  2019-03-31      100 

我想创建一个新列(重叠),该列将采用每行的值以及同一组中其他行的值(此处我要按人员列进行分组),它们的日期范围与该日期的范围重叠当前行。

为说明起见,第一行应为50(当前行的值)加100(因为第二行与第一行重叠),这使我们总共有150。在这里,请注意,我们没有包括第三行,因为第三行的日期范围与第一行不重叠。

我尝试过执行group_by(person)然后进行mutate(overlap),但是我不知道如何访问同一组中的其他行以了解它们是否与当前行重叠。我也尝试过研究Overlap()函数,但不确定如何利用它来获取所需的内容。

理想情况下,我想生成一个看起来像这样的表:

person    date1       date2     total amount  overlap 
  A     2019-03-01  2019-03-16       50         150   
  A     2019-03-10  2019-03-31      100         220   
  A     2019-03-20  2019-03-31       70         170   
  B     2019-03-01  2019-03-12      200         330   
  B     2019-03-01  2019-03-20      130         430   
  B     2019-03-16  2019-03-31      100         230   

1 个答案:

答案 0 :(得分:3)

我们可以group_by Person进行sumtotal_amount betweendate1中的date2

library(dplyr)

df %>%
  mutate_at(vars(starts_with("date")),  as.Date) %>%
  group_by(person) %>%
  mutate(overlap = purrr::map2_dbl(date1, date2, 
             ~sum(total_amount[between(date1, .x, .y) | between(date2, .x, .y)])))

#  person date1      date2      total_amount overlap
#  <fct>  <date>     <date>            <int>   <dbl>
#1 A      2019-03-01 2019-03-16           50     150
#2 A      2019-03-10 2019-03-31          100     220
#3 A      2019-03-20 2019-03-31           70     170
#4 B      2019-03-01 2019-03-12          200     330
#5 B      2019-03-01 2019-03-20          130     430
#6 B      2019-03-16 2019-03-31          100     230

数据

df <- structure(list(person = structure(c(1L, 1L, 1L, 2L, 2L, 2L), .Label = c("A", 
"B"), class = "factor"), date1 = structure(c(1L, 2L, 4L, 1L, 
1L, 3L), .Label = c("2019-03-01", "2019-03-10", "2019-03-16", 
"2019-03-20"), class = "factor"), date2 = structure(c(2L, 4L, 
4L, 1L, 3L, 4L), .Label = c("2019-03-12", "2019-03-16", "2019-03-20", 
"2019-03-31"), class = "factor"), total_amount = c(50L, 100L, 
70L, 200L, 130L, 100L)), class = "data.frame", row.names = c(NA, -6L))