R：找到每一行中所有非零元素的方差 [英] R: Find the Variance of all Non-Zero Elements in Each Row

问题描述

我有一个像这样的数据框d：

I have a dataframe d like this:

ID  Value1  Value2  Value3
1   20      25      0
2   2       0       0
3   15      32      16
4   0       0       0

我想做的是仅基于非零值来计算每个人（ID）的方差，并在不可能的情况下返回NA。

What I would like to do is calculate the variance for each person (ID), based only on non-zero values, and to return NA where this is not possible.

因此，例如，在此示例中，ID 1的方差为var（20，25），ID 2的
它将返回NA，因为您不能仅对一个条目计算方差，对于ID 3则为var将是var（15，32，16），对于ID 4，它将再次返回NULL，因为它根本没有数字可用来计算方差。

So for instance, in this example the variance for ID 1 would be var(20, 25), for ID 2 it would return NA because you can't calculate a variance on just one entry, for ID 3 the var would be var(15, 32, 16) and for ID 4 it would again return NULL because it has no numbers at all to calculate variance on.

我该怎么去对这个？我目前有以下（不完整的）代码，但这可能不是解决问题的最佳方法：

How would I go about this? I currently have the following (incomplete) code, but this might not be the best way to go about it:

len=nrow(d)
variances = numeric(len)
for (i in 1:len){
  #get all nonzero values in ith row of data into a vector nonzerodat here
  currentvar = var(nonzerodat)
  Variances[i]=currentvar
}

这是一个玩具示例，但是我实际上正在使用的数据集具有40多个不同的值列来计算方差，因此可以轻松缩放的东西会很棒。

Note this is a toy example, but the dataset I'm actually working with has over 40 different columns of values to calculate variance on, so something that easily scales would be great.

推荐答案

Data <- data.frame(ID = 1:4, Value1=c(20,2,15,0), Value2=c(25,0,32,0), Value3=c(0,0,16,0))

var_nonzero <- function(x) var(x[!x == 0])
apply(Data[, -1], 1, var_nonzero)

[1] 12.5   NA 91.0   NA

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