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Likert项)。我想对带有或不带有调查权重的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
我将针对许多变量执行此操作。因此,我决定将dplyr代码放入函数中,因此我只需要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))
这导致以下错误消息:
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()
来计数频率,但是我总是遇到一个错误(我检查过,plyr是在dplyr之前加载的,而不是在之后加载的-它也没有用。)有任何想法吗?我阅读了有关标准评估的小插图。但是,我总是遇到问题,不知道该怎么解决。
最佳答案
我认为您有一些嵌套的错误会给您带来麻烦。最大的一种是使用count()
而不是summarise()
。我猜你想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。如果您确实使用interp()
,则调用应该看起来像freq = interp(~n())
,即名称在对interp的调用之外,并且要内插的事物以~
开头。
关于r - 在函数中使用dplyr的问题(group_by),我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/28157919/