如何在一个函数中的两个变量中使用tabyl()? [英] How to use tabyl() with two variables within a function?

问题描述

我正在制作两个包含很多变量的表，因此希望编写使用看门人程序包中的tabyl()函数并映射到我感兴趣的变量上.

I'm making two tables that include lots of variables, so am looking to write functions that use tabyl() from the janitor package and map over the variables I'm interested in.

第一个功能运行正常:

cars = datasets::mtcars

first_table = function(variable){
  
  tabyl(variable, show_na = FALSE) %>% 
  adorn_pct_formatting(digits = 1) 
  
}

first_table(cars$vs)

第二个表的生成方式几乎相同，但应生成两个变量和行百分比的交叉表，而不是代表单个变量的表.这段代码和输出表示我正在尝试使用我的函数进行的操作:

The second table is produced in almost the same way, but should produce the cross-tabs of two variables and row percents instead of a table representing a single variable. This code and output represents what I'm trying to do with my function:

cars %>% 
  tabyl(vs, am, show_na = FALSE) %>% 
  adorn_percentages("row") %>% 
  adorn_pct_formatting(digits = 1) %>% 
  adorn_ns()

但是，当我将其编写为函数时，tabyl()函数似乎只想识别第一个变量:

When I write this as a function, however, it seems like the tabyl() function only wants to recognize the first variable:

second_table = function(variable1, variable2){
  
  tabyl(variable1, variable2, show_na = FALSE) %>% 
  adorn_percentages("row") %>% 
  adorn_pct_formatting(digits = 1) %>% 
  adorn_ns() 
  
}

second_table(cars$vs, cars$am)

我不太清楚问题出在哪里，我想知道如何编辑此函数，以便为我提供2x2表格，其中包含我可以在没有上述功能的情况下生成的行百分比.

I'm not quite sure what the issue is, and am wondering how I can edit this function to give me the 2x2 table with row percents that I was able to produce without a function above.

非常感谢您的帮助.

推荐答案

而不是传递列值，而是传递未加引号的列名，并使用curl_curly运算符 {{}}

Instead of passing column values, pass the unquoted column names and evaluate with curly_curly operator {{}}

second_table <- function(dat, variable1, variable2){
 dat %>% 
  tabyl({{variable1}}, {{variable2}}, show_na = FALSE) %>% 
  adorn_percentages("row") %>% 
  adorn_pct_formatting(digits = 1) %>% 
   adorn_ns() 

 }

-测试

second_table(cars, vs, am)
#  vs        0         1
#  0 66.7% (12) 33.3% (6)
#  1 50.0%  (7) 50.0% (7)

注意:最好也将数据集名称作为参数传递

NOTE: It is better to pass dataset name also as an argument

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