Data.Table 按组滚动连接

Question

如何找到每个（loc.x、loc.y）对的最后值，test.day之前？

dt <- data.table( 
  loc.x = as.integer(c(1, 1, 3, 1, 3, 1)),
  loc.y = as.integer(c(1, 2, 1, 2, 1, 2)),
  time = as.IDate(c("2015-03-11", "2015-05-10", "2015-09-27",
                    "2015-11-25", "2014-09-13", "2015-08-19")), 
  value = letters[1:6]
)

setkey(dt, loc.x, loc.y, time)
test.day <- as.IDate("2015-10-01")

需要的输出：

   loc.x loc.y value
1:     1     1     a
2:     1     2     f
3:     3     1     c

Answer 1

另一种选择是使用last 函数：

dt[, last(value[time < test.day]), by = .(loc.x, loc.y)]

给出：

   loc.x loc.y V1
1:     1     1  a
2:     1     2  f
3:     3     1  c

Answer 2

您可以首先将time < test.day 所在的行进行子集化（这应该非常有效，因为它不是按组完成的），然后选择每个组的最后一个value。为此，您可以使用 tail(value, 1L) 或按照 Floo0 的建议使用 value[.N]，结果是：

dt[time < test.day, tail(value, 1L), by = .(loc.x, loc.y)]
#   loc.x loc.y V1
#1:     1     1  a
#2:     1     2  f
#3:     3     1  c

或

dt[time < test.day, value[.N], by = .(loc.x, loc.y)]

请注意，这是有效的，因为数据是根据setkey(dt, loc.x, loc.y, time) 排序的。

Answer 3

这是另一个在创建查找表后使用滚动联接的选项

indx <- data.table(unique(dt[ ,.(loc.x, loc.y)]), time = test.day)  
dt[indx, roll = TRUE, on = names(indx)]
#    loc.x loc.y       time value
# 1:     1     1 2015-10-01     a
# 2:     1     2 2015-10-01     f
# 3:     3     1 2015-10-01     c

---

或@eddi 建议的非常相似的选项

dt[dt[, .(time = test.day), by = .(loc.x, loc.y)], roll = T, on = c('loc.x', 'loc.y', 'time')]

---

或者一个效率较低的班轮，因为它会按组调用[.data.table

dt[, 
    .SD[data.table(test.day), value, roll = TRUE, on = c(time = "test.day")], 
    by = .(loc.x, loc.y)
  ]
#    loc.x loc.y V1
# 1:     1     1  a
# 2:     1     2  f
# 3:     3     1  c