问题描述
我有一个整数数据框，它是所有 n 个选择 1...n 的 3 种组合的子集.例如，对于 n=5，它类似于:
I have a data frame of integers that is a subset of all of the n choose 3 combinations of 1...n.E.g., for n=5, it is something like:
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 2 4
[3,] 1 2 5
[4,] 1 3 4
[5,] 1 3 5
[6,] 1 4 5
[7,] 2 1 3
[8,] 2 1 4
[9,] 2 1 5
[10,] 2 3 4
[11,] 2 3 5
[12,] 2 4 5
[13,] 3 1 2
[14,] 3 1 4
[15,] 3 1 5
[16,] 3 2 4
[17,] 3 2 5
[18,] 3 4 5
[19,] 4 1 2
[20,] 4 1 3
[21,] 4 1 5
[22,] 4 2 3
[23,] 4 2 5
[24,] 4 3 5
[25,] 5 1 2
[26,] 5 1 3
[27,] 5 1 4
[28,] 5 2 3
[29,] 5 2 4
[30,] 5 3 4
我想做的是删除任何具有重复组合的行，而不管顺序如何.例如，[1,] 1 2 3 与 [1,] 2 1 3 与 [1,] 3 1 2 相同代码>.
What I'd like to do is remove any rows with duplicate combinations, irrespective of ordering. E.g., [1,] 1 2 3 is the same as [1,] 2 1 3 is the same as [1,] 3 1 2.
unique, duplicated, &c.似乎没有考虑到这一点.此外，我正在处理大量数据(n 为 ~750)，因此它应该是一个非常快的操作.是否有任何基本函数或包可以做到这一点?
unique, duplicated, &c. don't seem to take this into account. Also, I am working with quite a large amount of data (n is ~750), so it ought to be a pretty fast operation. Are there any base functions or packages that can do this?
推荐答案
先在行内排序，然后使用重复，见下图:
# example data
dat = matrix(scan('data.txt'), ncol = 3, byrow = TRUE)
# Read 90 items
dat[ !duplicated(apply(dat, 1, sort), MARGIN = 2), ]
# [,1] [,2] [,3]
# [1,] 1 2 3
# [2,] 1 2 4
# [3,] 1 2 5
# [4,] 1 3 4
# [5,] 1 3 5
# [6,] 1 4 5
# [7,] 2 3 4
# [8,] 2 3 5
# [9,] 2 4 5
# [10,] 3 4 5
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