[英]R dplyr: how to use ... with summarize(across()) when ... will refer to a variable name within the data?
I want to have a flexible function using summarize
in which:我想要使用
summarize
的灵活功能,其中:
A good example is the user providing fun=weighted.mean()
and specifying the weight argument w
.一个很好的例子是用户提供
fun=weighted.mean()
并指定权重参数w
。
For now, I am trying with the ...
.现在,我正在尝试使用
...
. The problem is that I don't find a way to have that ...
refer to a variable within the data-frame?问题是我没有找到一种方法来
...
引用数据框中的变量? The example below is given using across()
, but the same happens if I use instead summarize_at()
下面的示例是使用
across()
给出的,但如果我改为使用summarize_at()
也会发生同样的情况
Thanks!!谢谢!!
library(tidyverse)
fo1 <- function(df, fun=mean, ...){
df %>%
group_by(Species) %>%
summarise(across(starts_with("sepal"), fun, ...))
}
fo1(iris)
#> `summarise()` ungrouping output (override with `.groups` argument)
#> # A tibble: 3 x 3
#> Species Sepal.Length Sepal.Width
#> <fct> <dbl> <dbl>
#> 1 setosa 5.01 3.43
#> 2 versicolor 5.94 2.77
#> 3 virginica 6.59 2.97
fo1(iris, fun=weighted.mean)
#> `summarise()` ungrouping output (override with `.groups` argument)
#> # A tibble: 3 x 3
#> Species Sepal.Length Sepal.Width
#> <fct> <dbl> <dbl>
#> 1 setosa 5.01 3.43
#> 2 versicolor 5.94 2.77
#> 3 virginica 6.59 2.97
fo1(iris, fun=weighted.mean, w=Petal.Length)
#> Error: Problem with `summarise()` input `..1`.
#> x object 'Petal.Length' not found
#> ℹ Input `..1` is `across(starts_with("sepal"), fun, ...)`.
#> ℹ The error occurred in group 1: Species = "setosa".
fo1(iris, fun=weighted.mean, w=.data$Petal.Length)
#> Error: Problem with `summarise()` input `..1`.
#> x 'x' and 'w' must have the same length
#> ℹ Input `..1` is `across(starts_with("sepal"), fun, ...)`.
#> ℹ The error occurred in group 1: Species = "setosa".
Created on 2020-11-10 by the reprex package (v0.3.0)由reprex 包(v0.3.0) 于 2020 年 11 月 10 日创建
You need to pass the exact value of additional arguments.您需要传递附加参数的确切值。
.data$Petal.Length
is NULL
. .data$Petal.Length
为NULL
。
library(dplyr)
fo1 <- function(df, fun=mean, ...){
df %>%
summarise(across(starts_with("sepal"), fun, ...))
}
fo1(iris, fun=weighted.mean, w= iris$Petal.Length)
# Sepal.Length Sepal.Width
#1 6.180167 2.970197
This is ugly, but works.这很丑陋,但有效。
> fo1 <- function(df, fun=mean, ...){
+ w <- df %>% pull(...)
+ df %>%
+ summarise(across(starts_with("Sepal"), fun, w))
+ }
> fo1(iris, fun=weighted.mean, Petal.Length)
Sepal.Length Sepal.Width
1 6.180167 2.970197
Following on from Paul's suggestion in the comments above, this seems to be a general solution:继保罗在上述评论中的建议之后,这似乎是一个通用的解决方案:
fo1 <- function(df, fun=mean, ...){
df %>%
summarise(across(starts_with("Sepal"), fun, !!!enquos(...)))
}
> fo1(iris, fun=weighted.mean, Petal.Length)
Sepal.Length Sepal.Width
1 6.180167 2.970197
> fo1(iris, fun=mean)
Sepal.Length Sepal.Width
1 5.843333 3.057333
I tried several combinations of !!
我尝试了几种组合
!!
, !!!
,
!!!
, enquo()
and enquos()
but must have missed that one. ,
enquo()
和enquos()
但一定错过了那个。
enquos
will return a list of quoted expressions. enquos
将返回带引号的表达式列表。 The unquote-splice operator, !!!
取消引用拼接运算符,
!!!
, will unquote each element as an argument to the function call. , 将取消引用每个元素作为函数调用的参数。
library(tidyverse)
fo1 <- function(df, fun = mean, ...) {
df %>%
summarise(across(starts_with("sepal"), fun, !!!enquos(...)))
}
iris %>%
group_by(Species) %>%
fo1(fun = weighted.mean, w = Petal.Length, na.rm = TRUE)
#> # A tibble: 3 x 3
#> Species Sepal.Length Sepal.Width
#> <fct> <dbl> <dbl>
#> 1 setosa 5.02 3.44
#> 2 versicolor 5.98 2.79
#> 3 virginica 6.64 2.99
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