本文介绍了在 dplyr 的函数中使用变量名的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我想在 dplyr 的函数中使用变量名作为字符串.请看下面的例子:

I want to use variable names as strings in functions of dplyr. See the example below:

df <- data.frame(
      color = c("blue", "black", "blue", "blue", "black"),
      value = 1:5)
filter(df, color == "blue")

它工作得很好,但我想通过字符串来引用color,就像这样:

It works perfectly, but I would like to refer to color by string, something like this:

var <- "color"
filter(df, this_probably_should_be_a_function(var) == "blue").

我很乐意以任何方式做到这一点,并且非常乐意使用易于阅读的 dplyr 语法.

I would be happy, to do this by any means and super-happy to make use of easy-to-read dplyr syntax.

推荐答案

在较新的版本中,我们可以使用我们可以创建引用的变量然后取消引用(UQ!!) 用于评估

In the newer versions, we can use we can create the variables as quoted and then unquote (UQ or !!) for evaluation

var <- quo(color)
filter(df, UQ(var) == "blue")
#   color value
#1  blue     1
#2  blue     3
#3  blue     4

由于运算符的优先级,我们可能需要 () 来包裹 !!

Due to operator precedence, we may require () to wrap around !!

filter(df, (!!var) == "blue")
#   color value
#1  blue     1
#2  blue     3
#3  blue     4

在新版本中,||有更高的优先级,所以

With new version, || have higher precedence, so

filter(df, !! var == "blue")

应该有效(正如@Moody_Mudskipper 评论的那样)

should work (as @Moody_Mudskipper commented)

我们也可以使用:

 filter(df, get(var, envir=as.environment(df))=="blue")
 #color value
 #1  blue     1
 #2  blue     3
 #3  blue     4

重新排列解决方案的顺序

Rearranged the order of solutions

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08-23 02:25