在函数中使用dplyr时出现问题（分组依据）

我想使用dplyr进行一些数据操作。背景：我有一个调查权重和一系列变量（主要是likert项目）。我想对每个类别的频率和百分比加上和不加调查权重

作为一个例子，让我们使用频率作为性别变量。结果应该是：

 gender freq    freq.weighted
    1       292     922.2906
    2       279     964.7551
    9         6      21.7338

我将对许多变量执行此操作。因此，我决定将dplyr代码放在函数中，因此我只需更改变量并减少类型

#exampledata
gender<-c("2","2","1","2","2","2","2","2","2","2","2","2","1","1","2","2","2","2","2","2","1","2","2","2","2","2","2","2","2","2")
survey_weight<-c("2.368456","2.642901","2.926698","3.628653","3.247463","3.698195","2.776772","2.972387","2.686365","2.441820","3.494899","3.133106","3.253514","3.138839","3.430597","3.769577","3.367952","2.265350","2.686365","3.189538","3.029999","3.024567","2.972387","2.730978","4.074495","2.921552","3.769577","2.730978","3.247463","3.230097")
test_dataframe<-data.frame(gender,survey_weight)

#function
weighting.function<-function(dataframe,variable){
  test_weighted<- dataframe %>% 
    group_by_(variable) %>% 
    summarise_(interp(freq=count(~weight)),
               interp(freq_weighted=sum(~weight)))
  return(test_weighted)
}

result_dataframe<-weighting.function(test_dataframe,"gender")

#this second step was left out in this example:
#mutate_(perc=interp(~freq/sum(~freq)*100),perc_weighted=interp(~freq_weighted/sum(~freq_weighted)*100))

我试过很多不同的东西。首先，我使用

freq=n（）

有什么想法吗？我读了关于标准评估的小插曲。但是，我总是遇到问题，不知道什么是解决方案。
我认为你有一些嵌套的错误，这导致了你的问题。最大的一个是使用
count（）
而不是
summary（）
。我猜你想要
n（）
：

weighting.function%
分组依据（变量）%>%
总结_(
freq=~n（），
频率加权=~总和（调查加权）
)
}
加权函数（测试数据帧，~性别）

您还使用了一些不必要的
interp（）
。如果确实使用了
interp（）
，则调用应类似于
freq=interp（~n（））
，即名称不在对interp的调用范围内，而要插入的内容以
~
开头

Error in UseMethod("group_by_") : 
  no applicable method for 'group_by_' applied to an object of class "formula" 

weighting.function <- function(dataframe, variable){
  dataframe %>% 
    group_by_(variable) %>% 
    summarise_(
      freq = ~n(),
      freq_weighted = ~sum(survey_weight)
    )
}

weighting.function(test_dataframe, ~gender)