在矩阵中按组(行名)对列求和 [英] Sum columns by group (row names) in a matrix

问题描述

假设我有一个名为 x 的矩阵.

Let's say I have a matrix called x.

x <- structure(c(1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1), 
.Dim = c(5L, 4L), .Dimnames = list(c("Cake", "Pie", "Cake", "Pie", "Pie"),
c("Mon", "Tue", "Wed", "Thurs"))) 

x
     Mon   Tue   Wed   Thurs
Cake   1     0     1      1
Pie    0     0     1      1
Cake   1     1     0      1
Pie    0     0     1      1
Pie    0     0     1      1

我想对按行名分组的每一列求和:

I want to sum each column grouped by row names:

     Mon   Tue   Wed   Thurs
Cake   2     1     1      2
Pie    0     0     3      3

我尝试过使用 addmargins(x)，但这只是给了我每列和每行的总和.有什么建议?我搜索了其他问题，但无法弄清楚.

I've tried using addmargins(x), but that just gives me the sum of each column and row. Any suggestions? I searched other questions, but couldn't figure this out.

推荐答案

这是一个向量化的基础解决方案

Here's a vectorized base solution

rowsum(df, row.names(x))
#      Mon Tue Wed Thurs
# Cake   2   1   1     2
# Pie    0   0   3     3

或 data.table 版本使用 keep.rownames = TRUE 以便将您的行名转换为列

Or data.table version using keep.rownames = TRUE in order to convert your row names to a column

library(data.table)
as.data.table(x, keep.rownames = TRUE)[, lapply(.SD, sum), by = rn]
#      rn Mon Tue Wed Thurs
# 1: Cake   2   1   1     2
# 2:  Pie   0   0   3     3

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