dplyr - 使用列名作为函数参数 [英] dplyr - using column names as function arguments

问题描述

对于数据框，我使用 dplyr 来聚合一些列，如下所示.

With a data frame, I'm using dplyr to aggregate some column like below.

> data <- data.frame(a=rep(1:2,3), b=c(6:11))
> data
  a  b
1 1  6
2 2  7
3 1  8
4 2  9
5 1 10
6 2 11
> data %>% group_by(a) %>% summarize(tot=sum(b))
# A tibble: 2 x 2
      a   tot
  <int> <int>
1     1    24
2     2    27

这是完美的.但是我想为此创建一个可重用的函数，以便可以将列名作为参数传递.

This is perfect. However I want to create a re-usable function for this such that a column name can be passed as argument.

查看此处等相关问题的答案，我尝试了以下操作.

Looking at answers to related questions like here, I tried the following.

sumByColumn <- function(df, colName) {
  df %>%
  group_by(a) %>%
  summarize(tot=sum(colName))
  df
}

但是我无法让它工作.

> sumByColumn(data, "b")

 Error in summarise_impl(.data, dots) : 
  Evaluation error: invalid 'type' (character) of argument. 

> sumByColumn(data, b)

 Error in summarise_impl(.data, dots) : 
  Evaluation error: object 'b' not found. 
> 

推荐答案

这可以使用最新的 dplyr 语法(可以在 github):

This can work using the latest dplyr syntax (as can be seen on github):

library(dplyr)
library(rlang)
sumByColumn <- function(df, colName) {
  df %>%
    group_by(a) %>%
    summarize(tot = sum(!! sym(colName)))
}

sumByColumn(data, "b")
## A tibble: 2 x 2
#      a   tot
#  <int> <int>
#1     1    24
#2     2    27

另一种将 b 指定为变量的方法:

And an alternative way of specifying b as a variable:

library(dplyr)
sumByColumn <- function(df, colName) {
  myenc <- enquo(colName)
  df %>%
    group_by(a) %>%
    summarize(tot = sum(!!myenc))
}

sumByColumn(data, b)
## A tibble: 2 x 2
#      a   tot
#  <int> <int>
#1     1    24
#2     2    27

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