如何将函数应用于数据帧中所有行的组合？ [英] How to apply a function to all combinations of rows in a data frame?

问题描述

我无法解决以下有关下面的（通过限制列数的简化）数据框注释的问题。

I have trouble solving the following problem concerning the (simplified by limiting number of columns) data frame 'annotations' below.

require(irr)
# data
annotations <- read.table(text = "Obj1    Obj2    Obj3
Rater1     a       b       c
Rater2     a       b       b
Rater3     a       b       c", header = TRUE, stringsAsFactors = FALSE)

我想将irr包中的同意函数应用于所有行的组合（而不是排列），结果如下。

I would like to apply the function agree from the irr package to all combinations (not permutations) of rows, resulting in the following.

Agreement rater 1-2: 67%
Agreement rater 1-3: 100%
Agreement rater 2-3: 67%

我需要在行的所有组合上运行一个函数，该函数将需要访问多个/所有列。

I need to run a function on all combinations of rows and the function would need to access a number of/all columns.

我已经解决了部分问题的答案；我已经生成了运行 combn（rownames（annotations），2）的组合的列表，但是我看不到如何在不编写低效的for循环的情况下使用此列表。

I have worked out parts of the answer to the problem; I have generated a list of combinations running combn(rownames(annotations), 2), but I don't see how to use this list without writing inefficient for loops.

我尝试申请，就像 apply（注解，1，同意）一样，但是我只能使它起作用

I have tried apply, as in apply(annotations, 1, agree), but I can only get this to work on one row, not the combinations mentioned before.

有人知道如何进行吗？

更新：根据您的建议，以下解决方案有效。 （我使用了irr软件包中的 kappa2 而不是 agree ，但是主要问题的解决方案仍然相同。 ）

UPDATE: The following solution, based on your suggestions, works. (I have used kappa2 from the irr package instead of agree, but the solution to the main question remains the same.)

require(irr) #require the irr library for agreement calculations
annotations <- read.table(text = "Obj1    Obj2    Obj3
Rater1     a       b       c
Rater2     a       b       b
Rater3     a       b       c
Rater4     c       a       a", header = TRUE, stringsAsFactors = FALSE)

annotations <- t(annotations) #transpose annotations (rows become columns and vice versa)
kappa_list <- combn(colnames(annotations), 2, FUN=function(x) kappa_list[[length(kappa_list)+1]] = kappa2(matrix(c(annotations[,x[1]], annotations[,x[2]]), ncol=2))$value) #fill kappa_list with all pairs of columns (combinations of 2 raters) in annotations and, per combination, add a value to kappa_list that consists of the value of kappa2 applied to the current combination of raters
kappa_list # display the list of values

推荐答案

您很近，您只需要改为 combn 的结果应用。我不知道您要指的是什么函数，但是如果插入函数，它应该也能起作用。

You are close, you just need to apply on the result of combn instead. I have no idea what function you are referring to, but this should work the same if you plug in your function.

首先，将结果另存为列表，因为添加名称（将两个条目合并在一起）会更容易：

First, save the results as a list instead, because it is easier to add names (which I am adding my combining the two entries together):

toCheck <- combn(rownames(annotations), 2, simplify = FALSE)

names(toCheck) <-
  sapply(toCheck, paste, collapse = " - ")

然后，使用 sapply 完成组合。在这里，我使用平均值进行比较，但是请在此处使用您需要的内容。如果返回的值不止一个，请使用 lapply 然后根据需要打印结果

Then, use sapply to work through your combinations. Here, I am using mean to do the comparison, but use what you need here. If you are returning more than a single value, use lapply then work with the result to print as desired

sapply(toCheck, function(x){
  mean(annotations[x[1], ] == annotations[x[2], ])
})

哪个返回：

Rater 1 - Rater 2 Rater 1 - Rater 3 Rater 2 - Rater 3 
        0.6666667         1.0000000         0.6666667 

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