select和group_by关于引用变量之间的Dplyr差异？ [英] Dplyr difference between select and group_by with respect to quoted variables?

问题描述

在当前版本的dplyr中，可以按值传递 select 参数：

In the current version of dplyr, select arguments can be passed by value:

variable <- "Species"
iris %>% 
    select(variable)

#       Species
#1       setosa
#2       setosa
#3       setosa
#4       setosa
#5       setosa
#6       setosa
#...

但是 group_by 参数不能按值传递：

But group_by arguments cannot be passed by value:

iris %>% 
    group_by(variable) %>% 
    summarise(Petal.Length = mean(Petal.Length))

# Error in grouped_df_impl(data, unname(vars), drop) : 
# Column `variable` is unknown

有记录的dplyr :: select行为是

iris %>% select(Species)

和记录的记录的dplyr :: group_by行为是

iris %>% 
    group_by(Species) %>% 
    summarise(Petal.Length = mean(Petal.Length))

• 为什么选择和 group_by 在按值传递参数方面有所不同吗？


• 为什么第一个 select 调用为何


• 为什么第一个 group_by 调用为什么不起作用？我试图找出 quo（）， enquo（）和的组合!! 我应该使用它来使其工作。


• Why are select and group_by different with respect to passing arguments by value?
• Why is the first select call working and will it continue to work in the future?
• Why is the first group_by call not working? I'm trying to figure out what combination of quo(), enquo() and !! I should use to make it work.

我需要这个，因为我想创建一个函数以分组变量作为输入参数，如果可能的话，分组变量应作为字符串给出，因为另外两个函数参数已经作为字符串给出。

I need this because I would like to create a function that takes a grouping variable as input parameter, if possible the grouping variable should be given as a character string, because two other function parameters are already given as character strings.

推荐答案

要将字符串作为符号或未经评估的代码传递，您必须首先将其解析为符号或quosure。您可以使用<$ c $ rlang 中的 sym 或 parse_expr 来解析和以后使用 !! 取消引用：

To pass string as symbol or unevaluated code, you have to first parse it to symbol or quosure. You can use sym or parse_expr from rlang to parse and later use !! to unquote:

library(dplyr)

variable <- rlang::sym("Species")
# variable <- rlang::parse_expr("Species")

iris %>% 
  group_by(!! variable) %>% 
  summarise(Petal.Length = mean(Petal.Length))

!! 是 UQ（）的快捷方式，它不引用表达式或符号。这允许变量仅在调用它的范围内进行评估，即 group_by 。

!! is a shortcut for UQ(), which unquotes the expression or symbol. This allows variable to be evaluated only within the scope of where it is called, namely, group_by.

sym 和 parse_expr 之间的差异，以及使用哪一个

Difference between sym and parse_expr and which one to use when?

简短的答案：在这种情况下没关系。

The short answer: it doesn't matter in this case.

长答案：

符号是引用R对象（基本上是对象的名称）的一种方式。因此 sym 与基R中的 as.name 相似。 parse_expr 另一方面将一些文本转换为R表达式。这类似于基本R中的 parse 。

A symbol is a way to refer to an R object, basically the "name" of an object. So sym is similar to as.name in base R. parse_expr on the other hand transforms some text into R expressions. This is similar to parse in base R.

表达式可以是 any R代码，而不是引用R对象的 just 代码。因此，您可以解析引用R对象的 code ，但是如果引用的对象确实可以将某些随机代码转换为 sym 不存在。

Expressions can be any R code, not just code that references R objects. So you can parse the code that references an R object, but you can't turn some random code into sym if the object that it references does not exist.

通常，当字符串引用对象时，您将使用 sym （尽管 parse_expr 也可以），并在尝试解析任何其他R代码时使用 parse_expr

In general, you will use sym when your string refers to an object (although parse_expr would also work), and use parse_expr when you are trying to parse any other R code for further evaluation.

对于此特定用例，变量应该是在引用一个对象，因此将其转换为 sym 即可。另一方面，将其解析为表达式也是可行的，因为当 code 被取消引用时，它将在 group_by 内部求值。 !! 。

For this particular use case, variable is supposed to be referencing an object, so turning it into a sym would work. On the other hand, parsing it as an expression would also work because that is the code that is going to be evaluated inside group_by when being unquoted by !!.

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