我有两个数据表，我正在尝试合并。一个是公司市场价值随时间变化的数据，另一个是公司股息历史。我试图找出每个公司每个季度支付了多少钱，然后将这个价值放在市场价值数据旁边。
library(magrittr)
library(data.table)
library(zoo)
library(lubridate)
set.seed(1337)
# data table of company market values
companies <-
data.table(companyID = 1:10,
Sedol = rep(c("91772E", "7A662B"), each = 5),
Date = (as.Date("2005-04-01") + months(seq(0, 12, 3))) - days(1),
MktCap = c(100 + cumsum(rnorm(5,5)),
50 + cumsum(rnorm(5,1,5)))) %>%
setkey(Sedol, Date)
# data table of dividends
dividends <-
data.table(DivID = 1:7,
Sedol = c(rep('91772E', each = 4), rep('7A662B', each = 3)),
Date = as.Date(c('2004-11-19', '2005-01-13', '2005-01-29',
'2005-10-01', '2005-06-29', '2005-06-30',
'2006-04-17')),
DivAmnt = rnorm(7, .8, .3)) %>%
setkey(Sedol, Date)
我相信这是一种可以使用data.table滚动连接的情况，例如：
dividends[companies, roll = "nearest"]
尝试获取看起来像的数据集
DivID Sedol Date DivAmnt companyID MktCap
1: NA 7A662B <NA> NA 6 61.21061
2: 5 7A662B 2005-06-29 0.7772631 7 66.92951
3: 6 7A662B 2005-06-30 1.1815343 7 66.92951
4: NA 7A662B <NA> NA 8 78.33914
5: NA 7A662B <NA> NA 9 88.92473
6: NA 7A662B <NA> NA 10 87.85067
7: 2 91772E 2005-01-13 0.2964291 1 105.19249
8: 3 91772E 2005-01-29 0.8472649 1 105.19249
9: NA 91772E <NA> NA 2 108.74579
10: 4 91772E 2005-10-01 1.2467408 3 113.42261
11: NA 91772E <NA> NA 4 120.04491
12: NA 91772E <NA> NA 5 124.35588
（请注意，我已按照确切的季度将股息与公司市场价值相匹配）
但我不确定如何执行它。如果roll是一个值，那么CRAN pdf对于数字是什么或应该是什么应该是相当模糊的（你能否通过日期？一个数字量化了前进的日子吗？obersvations的数量？）和更改rollends似乎没有得到我想要的东西。
最后，我最终将股息日期映射到季度末，然后加入。一个很好的解决方案，但如果我最终需要知道如何执行滚动连接，则无用。在你的回答中，你能描述一种情况，滚动连接是唯一的解决方案，并帮助我理解如何执行它们？
您可能希望使用与foverlaps的data.table函数重叠连接而不是滚动连接：
# create an interval in the 'companies' datatable
companies[, `:=` (start = compDate - days(90), end = compDate + days(15))]
# create a second date in the 'dividends' datatable
dividends[, Date2 := divDate]
# set the keys for the two datatable
setkey(companies, Sedol, start, end)
setkey(dividends, Sedol, divDate, Date2)
# create a vector of columnnames which can be removed afterwards
deletecols <- c("Date2","start","end")
# perform the overlap join and remove the helper columns
res <- foverlaps(companies, dividends)[, (deletecols) := NULL]
结果：
> res Sedol DivID divDate DivAmnt companyID compDate MktCap 1: 7A662B NA <NA> NA 6 2005-03-31 61.21061 2: 7A662B 5 2005-06-29 0.7772631 7 2005-06-30 66.92951 3: 7A662B 6 2005-06-30 1.1815343 7 2005-06-30 66.92951 4: 7A662B NA <NA> NA 8 2005-09-30 78.33914 5: 7A662B NA <NA> NA 9 2005-12-31 88.92473 6: 7A662B NA <NA> NA 10 2006-03-31 87.85067 7: 91772E 2 2005-01-13 0.2964291 1 2005-03-31 105.19249 8: 91772E 3 2005-01-29 0.8472649 1 2005-03-31 105.19249 9: 91772E NA <NA> NA 2 2005-06-30 108.74579 10: 91772E 4 2005-10-01 1.2467408 3 2005-09-30 113.42261 11: 91772E NA <NA> NA 4 2005-12-31 120.04491 12: 91772E NA <NA> NA 5 2006-03-31 124.35588
与此同时，data.table作者引入了非等连接（v1.9.8）。您也可以使用它来解决此问题。使用非equi连接只需要：
companies[, `:=` (start = compDate - days(90), end = compDate + days(15))]
dividends[companies, on = .(Sedol, divDate >= start, divDate <= end)]
得到预期的结果。
使用过的数据（与问题相同，但没有创建密钥）：
set.seed(1337)
companies <- data.table(companyID = 1:10, Sedol = rep(c("91772E", "7A662B"), each = 5),
compDate = (as.Date("2005-04-01") + months(seq(0, 12, 3))) - days(1),
MktCap = c(100 + cumsum(rnorm(5,5)), 50 + cumsum(rnorm(5,1,5))))
dividends <- data.table(DivID = 1:7, Sedol = c(rep('91772E', each = 4), rep('7A662B', each = 3)),
divDate = as.Date(c('2004-11-19','2005-01-13','2005-01-29','2005-10-01','2005-06-29','2005-06-30','2006-04-17')),
DivAmnt = rnorm(7, .8, .3))