子集具有逻辑值矩阵的数据帧 [英] Subset data frame with matrix of logical values

问题描述

问题

我有四个人的两个措施的数据，每个都有广泛的格式。这些措施是 x 和 y ，个人是 A，B，C，D 。数据框看起来像这样

I have data on two measures for four individuals each in a wide format. The measures are x and y and the individuals are A, B, C, D. The data frame looks like this

d <- data.frame(matrix(sample(1:100, 40, replace = F), ncol = 8))
colnames(d) <- paste(rep(c("x.", "y."),each = 4), rep(LETTERS[1:4], 2), sep ="")
d

  x.A x.B x.C x.D y.A y.B y.C y.D
1  56  65  42  96 100  76  39  26
2  19  93  94  75  63  78   5  44
3  22  57  15  62   2  29  89  79
4  49  13  95  97  85  81  60  37
5  45  38  24  91  23  82  83  72

现在，我想为每一行获得的价值是 y 对于最小值 x 的个人。

Now, would I would like to obtain for each row is the value of y for the individual with the lowest value of x.

所以在上面的例子中， code> x 在行 1 是针对个人 C 。因此，对于行 1 我想获得 yC ，这是 39 。

So in the example above, the lowest value of x in row 1 is for individual C. Hence, for row 1 I would like to obtain y.C which is 39.

在示例中，结果向量应为 39,63,89,81,83

In the example, the resulting vector should be 39, 63, 89, 81, 83.

方法

我试图通过首先生成 x 的 d 子集的矩阵。

I have tried to get to this by first generating a matrix of the subset of d for the values of x.

t(apply(d[,1:4], 1, function(x) min(x) == x))

       x.A   x.B   x.C   x.D
[1,] FALSE FALSE  TRUE FALSE
[2,]  TRUE FALSE FALSE FALSE
[3,] FALSE FALSE  TRUE FALSE
[4,] FALSE  TRUE FALSE FALSE
[5,] FALSE FALSE  TRUE FALSE

现在我想将此矩阵应用于子集值为 y 的数据框的子集。但是我找不到一种方法来实现这一点。

Now I wanted to apply this matrix to subset the subset of the data frame for the values of y. But I cannot find a way to achieve this.

任何帮助都非常感激。对于完全不同 - 更优雅的方法的建议也是非常受欢迎的。

Any help is much appreciated. Suggestions for a totally different - more elegant - approach are highly welcome too.

非常感谢！

推荐答案

我们使用以'x'（'dx'）和'y'（'dy'）开头的列子集数据集。使用 max.col ， cbind 与行一起获取dx每行中最小值的列索引索引并获取'dy'中的相应元素。

We subset the dataset with the columns starting with 'x' ('dx') and 'y' ('dy'). Get the column index of the minimum value in each row of 'dx' using max.col, cbind with the row index and get the corresponding elements in 'dy'.

 dx <- d[grep('^x', names(d))]
 dy <- d[grep('^y', names(d))]
 dy[cbind(1:nrow(dx),max.col(-dx, 'first'))]
 #[1] 39 63 89 81 83

可以轻松转换为函数

 get_min <- function(dat){
     dx <- dat[grep('^x', names(dat))]
     dy <- dat[grep('^y', names(dat))]
     dy[cbind(1:nrow(dx), max.col(-dx, 'first'))]
   }
get_min(d)
#[1] 39 63 89 81 83

---

或使用OP的应用

t(d[,5:8])[apply(d[,1:4], 1, function(x) min(x) == x)] 
#[1] 39 63 89 81 83

< h3> data

data

d <- structure(list(x.A = c(56L, 19L, 22L, 49L, 45L),
x.B = c(65L, 
93L, 57L, 13L, 38L), x.C = c(42L, 94L, 15L, 95L, 24L), 
x.D = c(96L, 
75L, 62L, 97L, 91L), y.A = c(100L, 63L, 2L, 85L, 23L), 
y.B = c(76L, 
78L, 29L, 81L, 82L), y.C = c(39L, 5L, 89L, 60L, 83L), 
y.D = c(26L, 
44L, 79L, 37L, 72L)), .Names = c("x.A", "x.B", "x.C", 
"x.D", 
"y.A", "y.B", "y.C", "y.D"), class = "data.frame", 
row.names = c("1", "2", "3", "4", "5"))

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