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我有两个大型数据集，唯一的共享特征是数字时间戳。我想按此时间戳合并数据帧，但数据收集的频率并不完全匹配，因此我需要允许它与最近的可能匹配合并。

作为一个简化的示例，这里有一个小数据集，其中包含一个值列、一些事件和一个 ID：

a<-c("150", "164", "175", "183", "195", "200", "205","213")
b<-c("start1","end1","start2", "end2", "start1", "end1", "start2", "end2")
c<-c("A","A","A", "A", "B", "B", "B", "B")

(data<-data.table(value = a, event = b, ID = c))

我希望能够通过值列将这个“数据”与这个数字系列（“次”）合并：

(times<-data.frame(value = c(seq(from = 150, to = 213, by = 3))))

以便它们通过 value 列中最接近的近似匹配合并以生成此最终数据框：

agoal<-c(seq(from = 150, to = 213, by = 3))
bgoal<-c("start1","","","","","end1","", "",
     "start2", "", "", "end2", "", "", "",
     "start1", "", "end1", "start2", "", "", "end2")
cgoal<-c("A","","","","","A","", "",
         "A", "", "", "A", "", "", "",
         "B", "", "B", "B", "", "", "B")

(goal<-data.frame(value = agoal, event = bgoal, ID = cgoal))

有没有办法做到这一点，特别是对于一个非常大的数据集（所以它不会使 R 崩溃）？

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2 回答 2

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data.table provides a roll join solution.

library(data.table)
setkey(data,value)
setkey(times,value)
data[times,roll = "nearest"]
#    value  event ID
# 1:   150 start1  A
# 2:   153 start1  A
# 3:   156 start1  A
# 4:   159   end1  A
# 5:   162   end1  A
# 6:   165   end1  A
# 7:   168   end1  A
# 8:   171 start2  A
# 9:   174 start2  A
#10:   177 start2  A
#11:   180   end2  A
#12:   183   end2  A
#13:   186   end2  A
#14:   189   end2  A
#15:   192 start1  B
#16:   195 start1  B
#17:   198   end1  B
#18:   201   end1  B
#19:   204 start2  B
#20:   207 start2  B
#21:   210   end2  B
#22:   213   end2  B

data:

a<-c("150", "164", "175", "183", "195", "200", "205","213")
b<-c("start1","end1","start2", "end2", "start1", "end1", "start2", "end2")
c<-c("A","A","A", "A", "B", "B", "B", "B")

data<-data.table(value = as.numeric(a), event = b, ID = c)

times<-data.table(value = c(seq(from = 150, to = 213, by = 3)))
于 2021-07-04T16:32:07.453 回答
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要通过最近匹配加入而不用近似匹配填充空白，fuzzyjoin 效果很好！

(end<-fuzzyjoin::difference_left_join(times, data, by = "value", max_dist = 1, distance_col= "distance"))
于 2021-07-04T17:58:11.393 回答