R-dplyr 0.4.1:如何通过函数中的列名进行汇总 [英] R - dplyr 0.4.1 : How to summarise by a column name in a function

问题描述

我需要创建一个函数，该函数可以使用其名称来 group_by 和 summary 列.我正在使用dplyr 0.4.1版(并且我无法更新)，所以看来我在其他主题上找到的解决方案不起作用...

I need to create a function that could group_by and summarise a data frame using the names of its columns. I'm working with dplyr version 0.4.1 (and I cannot update), so it looks like the solutions I've found on the other topics doesn't work...

这是我的示例:

data <- data.frame(section=rep(c("A","B"),3), quantity=c(6:11))
#I need to get this result : 
RESULT = data %>% group_by(section) %>% summarise(total=sum(quantity))

我实现了此功能，但出现错误:

I implemented this function, but I got an error :

# function : 
synthetize = function(x,column,measure){
  result = x %>% group_by(column) %>% summarise(total=sum(measure))
}
RESULT2=synthetize(data,column="section",measure="quantity")
RESULT2

我尝试了 eval ， get ，但这似乎无济于事

I tried eval, get, but it looks like this doesn't help

推荐答案

我们可以使用 rlang :: sym 将字符串转换为符号并评估( !! )

We can convert the string to symbol with rlang::sym and evaluate (!!)

library(tidyverse)
synthetize = function(x, column, measure){
     x %>% 
        group_by_at(column) %>%
        summarise(total=sum(!! rlang::sym(measure)))
   }

synthetize(data, column="section", measure="quantity")
# A tibble: 2 x 2
#  section total
#   <fct>   <int>
#1 A          24
#2 B          27

注意:这里我们使用OP的相同参数类型

NOTE: Here we use the OP's same argument type

如果我们使用的是 dplyr 的旧版本，则以下内容可能会有所帮助

If we are using older version of dplyr, may be the following would help

library(lazyeval)
synthetize2 = function(x, column, measure){

  x %>% 
     group_by_(column) %>%
     summarise(total = interp(~ sum(v1), v1 = as.name(measure)))


synthetize2(data, column='section', measure='quantity')

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