如何找到至少2个向量中常见的元素? [英] How to find elements common in at least 2 vectors?

问题描述

假设我有 5 个向量:

Say I have 5 vectors:

a <- c(1,2,3)
b <- c(2,3,4)
c <- c(1,2,5,8)
d <- c(2,3,4,6)
e <- c(2,7,8,9)

我知道我可以通过使用 Reduce() 和 intersect() 来计算它们之间的交集，就像这样:

I know I can calculate the intersection between all of them by using Reduce() together with intersect(), like this:

Reduce(intersect, list(a, b, c, d, e))
[1] 2

但是我怎样才能找到在至少 2 个向量中常见的元素?即:

But how can I find elements that are common in, say, at least 2 vectors? i.e.:

[1] 1 2 3 4 8

推荐答案

它比很多人想象的要简单得多.这应该是非常有效的.

It is much simpler than a lot of people are making it look. This should be very efficient.

1. 将所有内容放入向量中:

1. Put everything into a vector:

x <- unlist(list(a, b, c, d, e))

查找重复项

Look for duplicates

unique(x[duplicated(x)])
# [1] 2 3 1 4 8

和 sort(如果需要).

注意:如果列表元素中可能存在重复项(您的示例似乎没有暗示)，请将 x 替换为 x <- unlist(lapply(list(a, b, c, d, e), 唯一))

Note: In case there can be duplicates within a list element (which your example does not seem to implicate), then replace x with x <- unlist(lapply(list(a, b, c, d, e), unique))

由于 OP 表示对 n >= 2 的更通用解决方案感兴趣，我会这样做:

as the OP has expressed interest in a more general solution where n >= 2, I would do:

which(tabulate(x) >= n)

如果数据仅由示例中的自然整数(1、2 等)组成.如果不是:

if the data is only made of natural integers (1, 2, etc.) as in the example. If not:

f <- table(x)
names(f)[f >= n]

这现在离 James 解决方案不远了，但它避免了昂贵的 sort.它比计算所有可能的组合要快几英里.

This is now not too far from James solution but it avoids the costly-ish sort. And it is miles faster than computing all possible combinations.

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