基于存储在独立有序向量中的值对对数据帧进行子集 [英] Subset a data frame based on value pairs stored in independent ordered vectors

问题描述

我有一个 R 数据框，我需要从中提取数据子集.子集将基于数据框中的两列.例如:

I have an R dataframe that I need to subset data from. The subsetting will be based on two columns in the dataframe. For example:

A <- c(1,2,3,3,5,1)
B <- c(6,7,8,9,8,8)
Value <- c(9,5,2,1,2,2)
DATA <- data.frame(A,B,Value)

这是 DATA 的样子

This is how DATA looks

A B Value
1 6     9
2 7     5
3 8     2
3 9     1
5 8     2
1 8     2

我想要那些 (A,B) 组合为 (1,6) 和 (3,8) 的数据行.这些对存储为 A 和 B 的单独(有序)向量:

I want those rows of data for which (A,B) combination is (1,6) and (3,8). These pairs are stored as individual (ordered) vectors of A and B:

AList <- c(1,3)
BList <- c(6,8)

现在，我试图通过比较 AList 中是否存在 A 列来对数据进行子集化AND B 列存在于 BList 中

Now, I am trying to subset the data basically by comparing if A column is present in AList AND B column is present in BList

DATA[(DATA$A %in% AList & DATA$B %in% BList),]

子集化结果如下所示.除了值对 (1,6) 和 (3,8) 我还得到 (1,8).基本上，这个过滤器为我提供了 AList 和 BList 中所有组合的值对.我如何将其限制为 (1,6) 和 (3,8)?

The subsetted result is shown below. In addition to the value pairs (1,6) and (3,8) I am also getting (1,8). Basically, this filter has given me value pairs for all combinations in AList and BList. How do I restrict it to just (1,6) and (3,8)?

A B Value
1 6     9
3 8     2
1 8     2

这是我想要的结果:

A B Value
1 6     9
3 8     2

推荐答案

你可以试试 match 一个合适的 nomatch 参数:

You could try match which an appropriated nomatch argument:

sub <- match(DATA$A, AList, nomatch=-1) == match(DATA$B, BList, nomatch=-2)
sub
# [1]  TRUE FALSE  TRUE FALSE FALSE FALSE

DATA[sub,]
#  A B Value
#1 1 6     9
#3 3 8     2

基于 paste 的方法也是可能的:

A paste based approach would also be possible:

sub <- paste(DATA$A, DATA$B, sep=":") %in% paste(AList, BList, sep=":")
sub
# [1]  TRUE FALSE  TRUE FALSE FALSE FALSE

DATA[sub,]
#  A B Value
#1 1 6     9
#3 3 8     2

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