比较两列的组并返回索引匹配 R [英] Compare group of two columns and return index matches R

问题描述

非常感谢您的阅读.抱歉，我确信这是一项简单的任务.

Many thanks for reading. Apologies for what I'm sure is a simple task.

我有一个数据框:(已添加了不包含在比较中的额外列)

I have a dataframe: (Edited: Added extra column not to be included in comparison)

b = c(5, 6, 7, 8, 10, 11) 
c = c('david','alan','pete', 'ben', 'richard', 'edd') 
d = c('alex','edd','ben','pete','raymond', 'alan')
df = data.frame(b, c, d) 
df
   b       c       d
1  5   david    alex
2  6    alan     edd
3  7    pete     ben
4  8     ben    pete
5 10 richard raymond
6 11     edd    alan

我想将 c 和 d 列组与 d 和 c 列组进行比较.也就是说，对于一行，我想将 c 和 d 中的组合值与 d 和 c 中的组合值进行比较 用于所有其他行.

I want to compare the group of columns c and d with the group of columns d and c. That is, for one row, I want to compare the combined values in c and d with the combined values in d and c for all other rows.

(注意值可以是字符或整数)

(Note the values could either be characters or integers)

在这些匹配的地方，我想返回匹配的那些行的索引，最好是作为列表的列表.我需要能够访问索引而不参考列 c 或 d 中的值.

Where these match I want to return the index of those rows which match, preferably as a list of lists. I need to be able to access the indexes without referring to the values in column c or d.

即对于上述数据框，我的预期输出是:

I.e. for the above dataframe, my expected output would be:

c(c(2, 6), c(3, 4))
((2,6), (3,4))

作为:

Row 2: (c + d == alan + edd) = row 6: (d + c == edd + alan)
Row 3: (c + d == pete + ben) = row 4: (d + c == ben + pete)

我了解如何使用 match melt 确定两个单独列的匹配情况，但如果它们连接在一起并遍历所有可能的行组合，则不知道.

I understand how to determine the match case for two separate columns using match melt, but not if they are joined together and iterating over all possible row combinations.

我的设想是这样的:

lapply(1:6, function(x), ifelse((df$a & df$b) == (df$b & df$a), index(x), 0))

但显然这是不正确的，不会起作用.

But obviously that is incorrect and won't work.

我咨询了以下问题，但无法给出答案.我不知道从哪里开始.

I consulted the following questions but have been unable to formulate an answer. I have no idea where to begin.

匹配多列在不同的数据帧上并获得其他列作为结果

将两列与另外两列匹配

比较多个数据框中的两列行

R 比较所有列对的每个值

我怎样才能实现上述目标?

How can I achieve the above?

推荐答案

你可以做这样的事情.它根据 df 的列形成的唯一排序字符串拆分行索引 1:nrow(df).排序确保 A,B 和 B,A 被同等对待.

You could do something like this. It splits the row indices 1:nrow(df) according to unique sorted strings formed from the columns of df. The sorting ensures that A,B and B,A are treated identically.

duplist <- split(1:nrow(df),apply(df,1,function(r) paste(sort(r),collapse=" ")))

duplist
$`alan edd`
[1] 2 6

$`alex david`
[1] 1

$`ben pete`
[1] 3 4

$`raymond richard`
[1] 5

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