链接数据框架和矩阵 [英] Link data.frame and matrix

问题描述

我有一个 data.frame 和一个矩阵，具有相同的行和不同的列数。

I have a data.frame and a matrix with same row and different number of columns.

矩阵中的所有元素都是整数，但$ code> data.frame 在一些列中包含字符。

All elements in the matrix are integer but the data.frame includes character in some columns.

我想链接这些文件的行，即如果我删除矩阵中的一行将自动删除 data.frame 中的同一行，当我对 data.frame 其列之一，矩阵中的元素被相应地排序。

I want to link the rows of these file, i.e. if if I delete a row in the matrix the same row in the data.frame be deleted automatically or when I sort the elements of data.frame with one of its column, the elements in the matrix be sorted accordingly.

添加注释：我想保留矩阵作为整数矩阵，所以我不能使用 cbind 。

Added note: I want to keep the matrix as integer matrix so I can not use cbind.

推荐答案

（至少）有两个解决方案。简单的选择是创建一个新的 data.frame ，其中包括这两行：

There are (at least) two solutions to this. The easy option is to make a new data.frame which includes both rows as such:

样本数据

Sample data

set.seed(123)
df <- data.frame(ID = 1:26, Group = sample(c("A", "B"), 26, TRUE))
mat <- matrix(rnorm(78), ncol = 3, dimnames = list(1:26, paste0("Val", 1:3)))

创建新的 data.frame ，存储矩阵列的名称供以后参考：

Make new data.frame, storing names of matrix columns for later reference:

new_df <- cbind(df, mat)
mat_cols <- colnames(mat)

做一些子集：

new_df <- new_df[seq(1, 25, 2), ]

需要时提取矩阵：

as.matrix(new_df[, mat_cols])

另一个选项是使用S3或S4类。 Bioconductor包 Biobase 具有例如一个 ExpressionSet 类，可以容纳矩阵和表型数据，子集用于子集（尽管矩阵具有相反的行和列）。

The other option is to use an S3 or S4 class. The Bioconductor package Biobase has, for example, an ExpressionSet class which can hold a matrix and phenotype data, and subsetting works to subset both (though the matrix has the rows and columns the opposite way round).

如果你想这样做更简单（ ExpressionsSet 可以相对复杂，让你的头脑），这里是一个S3实现：

If you wanted to do that more simply (ExpressionsSets can be relatively complex to get your head around), here's an S3 implementation:

as.JoinedUp <- function(data_frame, matrix) {
  stopifnot(is.data.frame(data_frame), is.matrix(matrix), nrow(data_frame) == nrow(matrix))
  x <- list(data_frame = data_frame, matrix = matrix)
  class(x) <- "JoinedUp"
  x
}
`[.JoinedUp` <- function(x, i = NULL, j = NULL) {
  if (is.null(i)) {
    i <- 1:nrow(x$data_frame)
  }
  if (is.null(j)) {
    j <- union(colnames(x$data_frame), colnames(x$matrix))
  }
  stopifnot(is.character(j))
  x$data_frame <- x$data_frame[i, intersect(j, colnames(x$data_frame)), drop = FALSE]
  x$matrix <- x$matrix[i, intersect(j, colnames(x$matrix)), drop = FALSE]
  x
}
`[<-.JoinedUp` <- function(x, i = NULL, j = NULL, value) {
  if (is.null(j)) {
    j <- union(colnames(x$data_frame), colnames(x$matrix))
  }
  if (is.null(i)) {
    i <- 1:nrow(x$data_frame)
  }
  stopifnot(is.character(j))
  if (!is.matrix(value) & !is.data.frame(value)) {
    value <- as.data.frame(t(value), stringsAsFactors = FALSE)
  }
  stopifnot(ncol(value) == length(j))
  if (any(j %in% colnames(x$data_frame))) {
    df_cols <- intersect(j, colnames(x$data_frame))
    x$data_frame[i, df_cols] <- value[, match(df_cols, j)]
  }
  if (any(j %in% colnames(x$matrix))) {
    mat_cols <- intersect(j, colnames(x$matrix))
    x$matrix[i, mat_cols] <- data.matrix(value[, match(mat_cols, j)])
  }
  x
}

示例：

new_obj <- as.JoinedUp(df, mat)
new_obj[1:3, ]
new_obj[, c("ID", "Val1")]
new_obj[10:15, ]$matrix
new_obj <- new_obj[order(new_obj$matrix[, "Val1"]), ]
new_obj[1:5, c("ID", "Val1")] <- data.frame(ID = 20:24, Val1 = 0)

这只是你需要的骨架;您可能还需要定义 dim ， nrow ， ncol 等。

This is only a skeleton of what you'd need; you'd probably also want to define methods for dim, nrow, ncol, etc.

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