R：使用管道％>％和占位符进一步对选择进行子集 [英] R: Further subset a selection using the pipe %>% and placeholder

问题描述

我最近发现了管道操作员％>％，这样可以使代码更易读。以下是我的 MWE 。

I recently discovered the pipe operator %>%, which can make code more readable. Here is my MWE.

library(dplyr)                                          # for the pipe operator
library(lsr)                                            # for the cohensD function

set.seed(4)                                             # make it reproducible
dat <- data.frame(                                      # create data frame
    subj = c(1:6),
    pre  = sample(1:6, replace = TRUE),
    post = sample(1:6, replace = TRUE)
)

dat %>% select(pre, post) %>% sapply(., mean)           # works as expected

但是，在这种特殊情况下，我努力使用管道操作符

However, I struggle using the pipe operator in this particular case

dat %>% select(pre, post) %>% cohensD(.$pre, .$post)    # piping returns an error
cohensD(dat$pre, dat$post)                              # classical way works fine

为什么不可能使用占位符分组列。 code>结合 $ ？使用管道操作符％>％编写此行是否值得，还是使语法复杂？经典的写作方式似乎更加简洁。

Why is it not possible to subset columns using the placeholder .in combination with $? Is it worthwhile to write this line using a pipe operator %>%, or does it complicate syntax? The classical way of writing this seems more concise.

推荐答案

由于你要从一堆数据转变成一行）值，你总结一下。在一个dplyr管道中，您可以使用summaryize函数，在summary不需要子集的函数中，可以调用 pre 和 post

Since you're going from a bunch of data into one (row of) value(s), you're summarizing. in a dplyr pipeline you can then use the summarize function, within the summarize function you don't need to subset and can just call pre and post

像这样：

dat %>% select(pre, post) %>% summarize(CD = cohensD(pre, post)) 

（在这种情况下，select语句实际上不是必需的，但是我留下来显示它在管道中的工作原理）

(The select statement isn't actually necessary in this case, but I left it in to show how this works in a pipeline)

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