在mutate（）中为列函数使用变量 [英] Using variables for column functions in mutate()

问题描述

如何在dplyr字符串中使用变量代替列名？举例来说，我想向虹膜数据集中添加一列，称为sum，即Sepal.Length和Sepal.Width的总和。简而言之，我想要下面的代码的工作版本。

How can I use variables in place of column names in dplyr strings? As an example say I want to add a column to the iris dataset called sum that is the sum of Sepal.Length and Sepal.Width. In short I want a working version of the below code.

x = "Sepal.Length"
y = "Sepal.Width"
head(iris%>% mutate(sum = x+y))

<当前，运行代码将输出评估错误：二进制运算符的非数字参数，因为R将x和y评估为字符向量。如何改为让R将x和y评估为数据框的列名？我知道答案是使用某种形式的延迟评估，但是我在弄清楚如何配置它时遇到了麻烦。

Currently, running the code outputs "Evaluation error: non-numeric argument to binary operator" as R evaluates x and y as character vectors. How do I instead get R to evaluate x and y as column names of the dataframe? I know that the answer is to use some form of lazy evaluation, but I'm having trouble figuring out exactly how to configure it.

请注意，建议的重复项： dplyr-变异：使用动态变量名称不能解决此问题。重复项回答了以下问题：

Note that the proposed duplicate: dplyr - mutate: use dynamic variable names does not address this issue. The duplicate answers this question:

不是我的问题：我该怎么办：

var = "sum"
head(iris %>% mutate(var = Sepal.Length + Sepal.Width))

推荐答案

我认为推荐的方式是使用 sym ：

I think that recommended way is using sym:

iris %>% mutate(sum = !!sym(x) + !!sym(y)) %>% head

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