英文:
How to avoid ellipsis ... in dplyr?
问题
我想创建一个接受分组参数的函数。它可以是单个或多个变量。我希望它看起来像这样：
```R
wanted <- function(data, groups, other_params){
data %>% group_by( {{groups}} ) %>% count()
}
这只在给定单个组时有效，但在存在多个组时会出错。我知道可以使用省略号 ... 来实现以下功能（但我想要的语法是 groups = something）：
not_wanted <- function(data, ..., other_params){
data %>% group_by( ... ) %>% count()
}
以下是完整的代码：
library(dplyr)
library(magrittr)
iris$group2 <- rep(1:5, 30)
wanted <- function(data, groups, other_params){
data %>% group_by( {{groups}} ) %>% count()
}
not_wanted <- function(data, ..., other_params){
data %>% group_by( ... ) %>% count()
}
# 正常运行
wanted(iris, groups = Species )
not_wanted(iris, Species, group2)
# 无法正常运行
wanted(iris, groups = vars(Species, group2) )
wanted(iris, groups = c(Species, group2) )
wanted(iris, groups = vars("Species", "group2") )
# Error: Column `vars(Species, group2)` must be length 150 (the number of rows) or one, not 2
<details>
<summary>英文:</summary>
I want to create a function that takes a grouping argument. Which can be a single or multiple variables. I want it to look like this:
wanted <- function(data, groups, other_params){
data %>% group_by( {{groups}} ) %>% count()
}
This work only when a single group is given but breaks when there are multiple groups. I know it's possible to use the following with ellipsis `...` (But I want the syntax `groups = something`):
not_wanted <- function(data, ..., other_params){
data %>% group_by( ... ) %>% count()
}
Here is the entire code:
library(dplyr)
library(magrittr)
iris$group2 <- rep(1:5, 30)
wanted <- function(data, groups, other_params){
data %>% group_by( {{groups}} ) %>% count()
}
not_wanted <- function(data, ..., other_params){
data %>% group_by( ... ) %>% count()
}
works
wanted(iris, groups = Species )
not_wanted(iris, Species, group2)
doesn't work
wanted(iris, groups = vars(Species, group2) )
wanted(iris, groups = c(Species, group2) )
wanted(iris, groups = vars("Species", "group2") )
Error: Column vars(Species, group2) must be length 150 (the number of rows) or one, not 2
答案1
得分: 5
你们把事情弄得太复杂了，这样就可以正常工作：
library(tidyverse)
wanted <- function(data, groups){
data %>% count(!!!groups)
}
mtcars %>% wanted(groups = vars(mpg, disp, hp))
一个 tibble: 31 x 4
mpg disp hp n
1 10.4 460 215 1
2 10.4 472 205 1
3 13.3 350 245 1
4 14.3 360 245 1
5 14.7 440 230 1
6 15 301 335 1
7 15.2 276. 180 1
8 15.2 304 150 1
9 15.5 318 150 1
10 15.8 351 264 1
… 其他 21 行
英文:
You guys are over complicating things, this works just fine:
library(tidyverse)
wanted <- function(data, groups){
data %>% count(!!!groups)
}
mtcars %>% wanted(groups = vars(mpg,disp,hp))
# A tibble: 31 x 4
mpg disp hp n
<dbl> <dbl> <dbl> <int>
1 10.4 460 215 1
2 10.4 472 205 1
3 13.3 350 245 1
4 14.3 360 245 1
5 14.7 440 230 1
6 15 301 335 1
7 15.2 276. 180 1
8 15.2 304 150 1
9 15.5 318 150 1
10 15.8 351 264 1
# … with 21 more rows
答案2
得分: 0
三重感叹号运算符和rlang包中的parse_quos函数将起作用。有关更多信息，请参见 https://stackoverflow.com/a/49941635/6086135
library(dplyr)
library(magrittr)
iris$group2 <- rep(1:5, 30)
vec <- c("Species", "group2")
wanted <- function(data, groups){
data %>% count(!!!rlang::parse_quos(groups, rlang::current_env()))
}
wanted(iris, vec)
#> # A tibble: 15 x 3
#> Species group2 n
#> <fct> <int> <int>
#> 1 setosa 1 10
#> 2 setosa 2 10
#> 3 setosa 3 10
#> 4 setosa 4 10
#> 5 setosa 5 10
#> 6 versicolor 1 10
#> 7 versicolor 2 10
#> 8 versicolor 3 10
#> 9 versicolor 4 10
#> 10 versicolor 5 10
#> 11 virginica 1 10
#> 12 virginica 2 10
#> 13 virginica 3 10
#> 14 virginica 4 10
#> 15 virginica 5 10
# Created on 2020-01-06 by the reprex package (v0.3.0)
英文:
The triple bang operator and parse_quos from the rlang package will do the trick. For more info, see e.g. https://stackoverflow.com/a/49941635/6086135
<!-- language-all: lang-r -->
library(dplyr)
library(magrittr)
iris$group2 <- rep(1:5, 30)
vec <- c("Species", "group2")
wanted <- function(data, groups){
data %>% count(!!!rlang::parse_quos(groups, rlang::current_env()))
}
wanted(iris, vec)
#> # A tibble: 15 x 3
#> Species group2 n
#> <fct> <int> <int>
#> 1 setosa 1 10
#> 2 setosa 2 10
#> 3 setosa 3 10
#> 4 setosa 4 10
#> 5 setosa 5 10
#> 6 versicolor 1 10
#> 7 versicolor 2 10
#> 8 versicolor 3 10
#> 9 versicolor 4 10
#> 10 versicolor 5 10
#> 11 virginica 1 10
#> 12 virginica 2 10
#> 13 virginica 3 10
#> 14 virginica 4 10
#> 15 virginica 5 10
<sup>Created on 2020-01-06 by the reprex package (v0.3.0)</sup>
答案3
得分: 0
以下是翻译好的部分：
这是另一种避免在函数调用中使用引号的选项。我承认它并不是很漂亮。
library(tidyverse)
wanted <- function(data, groups){
grouping <- gsub(x = rlang::quo_get_expr(enquo(groups)), pattern = "\\((.*)?\\)", replacement = "\")[-1]
data %>% group_by_at(grouping) %>% count()
}
iris$group2 <- rep(1:5, 30)
wanted(iris, groups = c(Species, group2) )
#> # A tibble: 15 x 3
#> # Groups: Species, group2 [15]
#> Species group2 n
#> <fct> <int> <int>
#> 1 setosa 1 10
#> 2 setosa 2 10
#> 3 setosa 3 10
#> 4 setosa 4 10
#> 5 setosa 5 10
#> 6 versicolor 1 10
#> 7 versicolor 2 10
#> 8 versicolor 3 10
#> 9 versicolor 4 10
#> 10 versicolor 5 10
#> 11 virginica 1 10
#> 12 virginica 2 10
#> 13 virginica 3 10
#> 14 virginica 4 10
#> 15 virginica 5 10
希望这对您有所帮助。
英文:
Here is another option to avoid quotations in the function call. I admit its not very pretty though.
library(tidyverse)
wanted <- function(data, groups){
grouping <- gsub(x = rlang::quo_get_expr(enquo(groups)), pattern = "\\((.*)?\\)", replacement = "\")[-1]
data %>% group_by_at(grouping) %>% count()
}
iris$group2 <- rep(1:5, 30)
wanted(iris, groups = c(Species, group2) )
#> # A tibble: 15 x 3
#> # Groups: Species, group2 [15]
#> Species group2 n
#> <fct> <int> <int>
#> 1 setosa 1 10
#> 2 setosa 2 10
#> 3 setosa 3 10
#> 4 setosa 4 10
#> 5 setosa 5 10
#> 6 versicolor 1 10
#> 7 versicolor 2 10
#> 8 versicolor 3 10
#> 9 versicolor 4 10
#> 10 versicolor 5 10
#> 11 virginica 1 10
#> 12 virginica 2 10
#> 13 virginica 3 10
#> 14 virginica 4 10
#> 15 virginica 5 10
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