提取data.table的段

Question

我有一个data.table,我需要从不同的行位置开始提取相等长度的段.最简单的方法是什么？例如:

x <- data.table(a=sample(1:1000,100), b=sample(1:1000,100))
r <- c(1,2,10,20,44)
idx <- lapply(r, function(i) {j <-which(x$a == i); if (length(j)>0) {return(j)} })
y <- lapply(idx, function(i) {if (!is.null(i)) x[i:(i+5)]})
do.call(rbind, y)
    a   b
1:  44  63
2:  96 730
3: 901 617
4: 446 370
5: 195 341
6: 298 411

这当然不是data.table做事的方式所以我希望有更好的方法吗？

编辑:根据下面的评论,我编辑它只是为了清楚,它们中的值a不一定是连续的,也不对应于行号.

Answer 1

不确定您是否已经知道行位置,或者是否要搜索它们.无论哪种方式,这应该涵盖两者.

require(data.table)
set.seed(1)
DT = data.table(a=sample(1:1000,20), b=sample(1:1000,20))
setkey(DT,a)
DT
#       a   b
#  1:  62 338
#  2: 175 593
#  3: 201 267
#  4: 204 478
#  5: 266 935
#  6: 372 212
#  7: 374 711
#  8: 380 184
#  9: 491 659
# 10: 572 651
# 11: 625 863
# 12: 657 380
# 13: 679 488
# 14: 707 782
# 15: 760 816
# 16: 763 404
# 17: 894 385
# 18: 906 126
# 19: 940  14
# 20: 976 107
r = c(201,380,760)
starts = DT[J(r),which=TRUE]  # binary search for items
                              # skip if the starting row numbers are known
starts
# [1]  3  8 15

选项1:制作行号序列,连接并进行一次查找DT(不需要键或二进制搜索只需按行号选择):

DT[unlist(lapply(starts,seq.int,length=5))]
#       a   b
#  1: 201 267
#  2: 204 478
#  3: 266 935
#  4: 372 212
#  5: 374 711
#  6: 380 184
#  7: 491 659
#  8: 572 651
#  9: 625 863
# 10: 657 380
# 11: 760 816
# 12: 763 404
# 13: 894 385
# 14: 906 126
# 15: 940  14

选项2:列出data.table子集,然后将rbind它们放在一起.这比选项1效率低,但为了完整性:

L = lapply(starts,function(i)DT[seq.int(i,i+4)])
L
# [[1]]
#      a   b
# 1: 201 267
# 2: 204 478
# 3: 266 935
# 4: 372 212
# 5: 374 711
# 
# [[2]]
#      a   b
# 1: 380 184
# 2: 491 659
# 3: 572 651
# 4: 625 863
# 5: 657 380
# 
# [[3]]
#      a   b
# 1: 760 816
# 2: 763 404
# 3: 894 385
# 4: 906 126
# 5: 940  14 

rbindlist(L)   # more efficient that do.call("rbind",L). See ?rbindlist.
#       a   b
#  1: 201 267
#  2: 204 478
#  3: 266 935
#  4: 372 212
#  5: 374 711
#  6: 380 184
#  7: 491 659
#  8: 572 651
#  9: 625 863
# 10: 657 380
# 11: 760 816
# 12: 763 404
# 13: 894 385
# 14: 906 126
# 15: 940  14