在循环中使用glue和dplyr获取级别名称

我尝试使用dplyr和glue在循环中从表中获取级别名称（我使用循环是因为我获得了大量变量以获得分组表和单个表），我在下面展示了一个示例：

library(dplyr)
library(glue)
var=c( "vs", "am")
for(i in var) {
bd=mtcars%>%
group_by(carb) %>%
 count_(i) %>%
      mutate(descripcion = glue("carb number:{carb} in: {i} with freq: {n},"))
print(bd) 
print(bd$descripcion)
}

我的结果是：

组别：碳水化合物[6]

---

我们可以使用

paste0

，因为它是矢量化的

library(dplyr)

mtcars%>% 
   count(carb, vs) %>%
   mutate(description = paste0("carb number: ",carb, " in: vs ", vs, 
                                " with freq: ", n))


#   carb    vs     n description                         
#  <dbl> <dbl> <int> <chr>                               
#1     1     1     7 carb number: 1 in: vs 1 with freq: 7
#2     2     0     5 carb number: 2 in: vs 0 with freq: 5
#3     2     1     5 carb number: 2 in: vs 1 with freq: 5
#4     3     0     3 carb number: 3 in: vs 0 with freq: 3
#5     4     0     8 carb number: 4 in: vs 0 with freq: 8
#6     4     1     2 carb number: 4 in: vs 1 with freq: 2
#7     6     0     1 carb number: 6 in: vs 0 with freq: 1
#8     8     0     1 carb number: 8 in: vs 0 with freq: 1

---

编辑

如果我们要计算不同的列，我们可以将变量转换为符号

var = c("vs", "am")
library(rlang)

map(var, function(x) mtcars%>% 
                       count(carb, !!sym(x)) %>%
                       mutate(description = paste0("carb number: ",carb, " in: ", 
                        x, " " , !!sym(x)," with freq: ", n)))

#[[1]]
# A tibble: 8 x 4
#   carb    vs     n description                         
#  <dbl> <dbl> <int> <chr>                               
#1     1     1     7 carb number: 1 in: vs 1 with freq: 7
#2     2     0     5 carb number: 2 in: vs 0 with freq: 5
#3     2     1     5 carb number: 2 in: vs 1 with freq: 5
#4     3     0     3 carb number: 3 in: vs 0 with freq: 3
#5     4     0     8 carb number: 4 in: vs 0 with freq: 8
#6     4     1     2 carb number: 4 in: vs 1 with freq: 2
#7     6     0     1 carb number: 6 in: vs 0 with freq: 1
#8     8     0     1 carb number: 8 in: vs 0 with freq: 1

#[[2]]
# A tibble: 9 x 4
#   carb    am     n description                         
#  <dbl> <dbl> <int> <chr>                               
#1     1     0     3 carb number: 1 in: am 0 with freq: 3
#2     1     1     4 carb number: 1 in: am 1 with freq: 4
#3     2     0     6 carb number: 2 in: am 0 with freq: 6
#4     2     1     4 carb number: 2 in: am 1 with freq: 4
#5     3     0     3 carb number: 3 in: am 0 with freq: 3
#6     4     0     7 carb number: 4 in: am 0 with freq: 7
#7     4     1     3 carb number: 4 in: am 1 with freq: 3
#8     6     1     1 carb number: 6 in: am 1 with freq: 1
#9     8     1     1 carb number: 8 in: am 1 with freq: 1

---

我们可以直接在列上使用

glue\u数据

而不需要任何循环

library(glue)
library(dplyr)
mtcars %>% 
 count(carb, vs) %>%
 mutate(description = glue_data(., "carb number: {carb} in: vs {vs} with freq: {n}"))
# A tibble: 8 x 4
#   carb    vs     n description                         
#  <dbl> <dbl> <int> <S3: glue>                          
#1     1     1     7 carb number: 1 in: vs 1 with freq: 7
#2     2     0     5 carb number: 2 in: vs 0 with freq: 5
#3     2     1     5 carb number: 2 in: vs 1 with freq: 5
#4     3     0     3 carb number: 3 in: vs 0 with freq: 3
#5     4     0     8 carb number: 4 in: vs 0 with freq: 8
#6     4     1     2 carb number: 4 in: vs 1 with freq: 2
#7     6     0     1 carb number: 6 in: vs 0 with freq: 1
#8     8     0     1 carb number: 8 in: vs 0 with freq: 1

---

@罗德里戈：你为什么需要使用循环？如图所示，粘贴0在没有任何循环的情况下工作。或者，如果您想使用

glue

，那么您可以使用

pmap

。我有大量的变量用于构造GROUPED表，我只展示了一个示例。无论您的表有多大，只要它遵循与

mtcars

相同的结构，这都应该有效。还要注意的是，我没有使用

groupby

I，而是将该变量包含在

count

中，以便它自动计算

carb

和

vs

中的每个唯一变量。你能试一下吗？让我们来。

library(dplyr)
library(glue)
library(purrr)

mtcars%>% 
   count(carb, vs) %>%
   mutate(description = pmap_chr(list(carb, vs, n), function(a, b, c) 
             glue("carb number: ",{a}, " in: vs ", {b}, " with freq: ", {c})))

var = c("vs", "am")
library(rlang)

map(var, function(x) mtcars%>% 
                       count(carb, !!sym(x)) %>%
                       mutate(description = paste0("carb number: ",carb, " in: ", 
                        x, " " , !!sym(x)," with freq: ", n)))

#[[1]]
# A tibble: 8 x 4
#   carb    vs     n description                         
#  <dbl> <dbl> <int> <chr>                               
#1     1     1     7 carb number: 1 in: vs 1 with freq: 7
#2     2     0     5 carb number: 2 in: vs 0 with freq: 5
#3     2     1     5 carb number: 2 in: vs 1 with freq: 5
#4     3     0     3 carb number: 3 in: vs 0 with freq: 3
#5     4     0     8 carb number: 4 in: vs 0 with freq: 8
#6     4     1     2 carb number: 4 in: vs 1 with freq: 2
#7     6     0     1 carb number: 6 in: vs 0 with freq: 1
#8     8     0     1 carb number: 8 in: vs 0 with freq: 1

#[[2]]
# A tibble: 9 x 4
#   carb    am     n description                         
#  <dbl> <dbl> <int> <chr>                               
#1     1     0     3 carb number: 1 in: am 0 with freq: 3
#2     1     1     4 carb number: 1 in: am 1 with freq: 4
#3     2     0     6 carb number: 2 in: am 0 with freq: 6
#4     2     1     4 carb number: 2 in: am 1 with freq: 4
#5     3     0     3 carb number: 3 in: am 0 with freq: 3
#6     4     0     7 carb number: 4 in: am 0 with freq: 7
#7     4     1     3 carb number: 4 in: am 1 with freq: 3
#8     6     1     1 carb number: 6 in: am 1 with freq: 1
#9     8     1     1 carb number: 8 in: am 1 with freq: 1

for (i in var) {
   print(mtcars%>% 
           count(carb, !!sym(i)) %>%
           mutate(description = paste0("carb number: ",carb, " in: ", i, " " , 
                                  !!sym(i), " with freq: ", n)))
}

library(glue)
library(dplyr)
mtcars %>% 
 count(carb, vs) %>%
 mutate(description = glue_data(., "carb number: {carb} in: vs {vs} with freq: {n}"))
# A tibble: 8 x 4
#   carb    vs     n description                         
#  <dbl> <dbl> <int> <S3: glue>                          
#1     1     1     7 carb number: 1 in: vs 1 with freq: 7
#2     2     0     5 carb number: 2 in: vs 0 with freq: 5
#3     2     1     5 carb number: 2 in: vs 1 with freq: 5
#4     3     0     3 carb number: 3 in: vs 0 with freq: 3
#5     4     0     8 carb number: 4 in: vs 0 with freq: 8
#6     4     1     2 carb number: 4 in: vs 1 with freq: 2
#7     6     0     1 carb number: 6 in: vs 0 with freq: 1
#8     8     0     1 carb number: 8 in: vs 0 with freq: 1

library(rlang)
library(purrr)
map(var, ~ mtcars %>%
             count(carb, !! sym(.x)) %>%
              mutate(description = glue_data(., 
                  "carb number: {carb} in: vs {.x} with freq: {n}")))