使用 dplyr::mutate() 在列子集上按行 cor()

set.seed(8)
df <- data.frame(
  A=sample(c(1:3), 10, replace=T), 
  B=sample(c(1:3), 10, replace=T),
  C=sample(c(1:3), 10, replace=T),
  D=sample(c(1:3), 10, replace=T),
  E=sample(c(1:3), 10, replace=T), 
  F=sample(c(1:3), 10, replace=T))

想要将列的子集传递到 dplyrmutate()并进行逐行计算，例如cor()获得 A-C 列和 D-F 列之间的相关性，但不知道如何实现。找到了灵感here https://stackoverflow.com/questions/28159143/add-column-with-row-wise-mean-over-selected-columns-using-dplyr, here https://stackoverflow.com/questions/21818181/applying-a-function-to-every-row-of-a-table-using-dplyr and here https://stackoverflow.com/questions/28751023/performing-dplyr-mutate-on-subset-of-columns，但仍然未能产生可接受的代码。例如，我尝试过这个：

require(plyr)
require(dplyr)
df %>%
  rowwise() %>%
  mutate(c=cor(.[[1:3]],.[[4:6]]))

你可以尝试

df %>% 
   rowwise() %>% 
   do(data.frame(., Cor=cor(unlist(.[1:3]), unlist(.[4:6]))))