如何进行数据表滚动联接？

Question

我有两个要合并的数据表。一个是关于时间的公司市场价值数据，另一个是关于时间的公司股息历史记录。我试图找出每个公司每个季度支付了多少钱，并将该价值随时间推移到市场价值数据旁边。

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)

我相信在这种情况下，您可以使用data.table滚动连接，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，我已将股息与确切的季度的公司市值进行了匹配）

但是我不确定如何执行它。该CRAN PDF格式相当含糊什么数，或者应该有，如果roll是一个值（你可以通过日期？有没有一个量化数天前进行？obersvations多少？）和改变rollends周围似乎并没有让我我想要的是。

最后，我最终将股息日期映射到其季度末，然后加入。一个很好的解决方案，但是如果我最终需要了解如何执行滚动联接，就没有用。在您的回答中，您能否描述滚动连接是唯一解决方案的情况，并帮助我理解如何执行它们？

Answer 1

代替滚动连接，您可能希望将重叠连接与data.tablefoverlaps函数一起使用：

# 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

同时，data.table作者引入了非等价联接（v1.9.8）。您也可以使用它来解决此问题。使用非等额联接，您只需要：

companies[, `:=` (start = compDate - days(90), end = compDate + days(15))]
dividends[companies, on = .(Sedol, divDate >= start, divDate <= end)]

获得预期的结果。

使用的数据（与问题中相同，但未创建密钥）：

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))