在函数中使用 dplyr 的问题 (group_by)

Question

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堆变量（主要是李克特项目）。我想在有和没有调查权重的情况下对每个类别的频率和百分比求和。

例如，让我们只使用频率作为性别变量。结果应该是这样的：

 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。所以，我决定将 dplyr 代码放在一个函数中，这样我只需要更改变量并减少输入即可。

#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))

这会导致以下错误消息：

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

我尝试了很多不同的东西。首先，我使用 freq=n() 来计算频率，但我总是得到一个错误（我检查过，plyr 是在 dplyr 之前加载的，而不是之后加载的 - 它也没有工作。）。

有什么想法吗？我阅读了关于标准评估的小插图。但是，我总是运行遇到问题并且不知道什么是解决方案。

Answer 1

我认为您有一些嵌套错误导致了问题。最大的一个是使用 count() 而不是 summarise()。我猜你想要 n():

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

weighting.function(test_dataframe, ~gender)

您还对 interp() 进行了一些不必要的使用。如果你确实使用 interp()，调用应该看起来像 freq = interp(~n())，即名称在对 interp 的调用之外，并且被插入的东西以 ~.

开头

在函数中使用 dplyr 的问题 (group_by)

Problems using dplyr in a function (group_by)

r

function

plyr

dplyr