在数据帧中成对计算有效观测值的数量(无NA) [英] Count the number of valid observations (no NA) pairwise in a data frame

问题描述

说我有一个像这样的数据框:

Say I have a data frame like this:

Df <- data.frame(
    V1 = c(1,2,3,NA,5),
    V2 = c(1,2,NA,4,5),
    V3 = c(NA,2,NA,4,NA)
)

现在，我想计算两个变量的每种组合的有效观察数.为此，我编写了一个函数 sharedcount :

Now I want to count the number of valid observations for every combination of two variables. For that, I wrote a function sharedcount:

sharedcount <- function(x,...){
    nx <- names(x)
    alln <- combn(nx,2)
    out <- apply(alln,2,
      function(y)sum(complete.cases(x[y]))
    )
    data.frame(t(alln),out)
}

这给出了输出:

> sharedcount(Df)
  X1 X2 out
1 V1 V2   3
2 V1 V3   1
3 V2 V3   2

很好，但是函数本身在大数据帧(600个变量和大约10000个观察值)上花费很长时间.我觉得我正在监督一种更简单的方法，尤其是因为cor(...，use ='pairwise')的运行速度要快得多，而它必须执行类似的操作:

All fine, but the function itself takes pretty long on big dataframes (600 variables and about 10000 observations). I have the feeling I'm overseeing an easier approach, especially since cor(...,use='pairwise') is running still a whole lot faster while it has to do something similar :

> require(rbenchmark)    
> benchmark(sharedcount(TestDf),cor(TestDf,use='pairwise'),
+     columns=c('test','elapsed','relative'),
+     replications=1
+ )
                           test elapsed relative
2 cor(TestDf, use = "pairwise")    0.25     1.0
1           sharedcount(TestDf)    1.90     7.6

任何提示都值得赞赏.

注意:使用Vincent的技巧，我编写了一个返回相同数据帧的函数.在下面的答案中输入代码.

Note : Using Vincent's trick, I wrote a function that returns the same data frame. Code in my answer below.

推荐答案

以下内容会更快:

x <- !is.na(Df)
t(x) %*% x

#       test elapsed relative
#    cor(Df)  12.345 1.000000
# t(x) %*% x  20.736 1.679708

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