如何使用 dplyr::pull 将 groupby 列转换为向量？

Question

我有一个 tibble，df，我想获取 tibble 并将其分组，然后使用 dplyr::pull 从分组的数据帧创建向量。我在下面提供了一个代表。

df 是基础 tibble。 df2 反映了我想要的输出。我只是不知道如何以编程方式到达那里。我尝试使用 pull 来实现此输出，但 pull 似乎无法识别 group_by 函数，而是从整个列中创建了一个向量。是我试图通过 dplyr 或 base r 实现的目标。注意 - new_col 应该是从 name 列创建的向量。

library(tidyverse)
library(reprex)

df <- tibble(group = c(1,1,1,1,2,2,2,3,3,3,3,3),
             name = c('Jim','Deb','Bill','Ann','Joe','Jon','Jane','Jake','Sam','Gus','Trixy','Don'),
             type = c(1,2,3,4,3,2,1,2,3,1,4,5))

df
#> # A tibble: 12 x 3
#>    group name   type
#>    <dbl> <chr> <dbl>
#>  1     1 Jim       1
#>  2     1 Deb       2
#>  3     1 Bill      3
#>  4     1 Ann       4
#>  5     2 Joe       3
#>  6     2 Jon       2
#>  7     2 Jane      1
#>  8     3 Jake      2
#>  9     3 Sam       3
#> 10     3 Gus       1
#> 11     3 Trixy     4
#> 12     3 Don       5

# Desired Output - New Col is a column of vectors

df2 <- tibble(group=c(1,2,3),name=c("Jim","Jane","Gus"), type=c(1,1,1), new_col = c("'Jim','Deb','Bill','Ann'","'Joe','Jon','Jane'","'Jake','Sam','Gus','Trixy','Don'"))
df2
#> # A tibble: 3 x 4
#>   group name   type new_col                         
#>   <dbl> <chr> <dbl> <chr>                           
#> 1     1 Jim       1 'Jim','Deb','Bill','Ann'        
#> 2     2 Jane      1 'Joe','Jon','Jane'              
#> 3     3 Gus       1 'Jake','Sam','Gus','Trixy','Don'
Created on 2020-11-14 by the reprex package (v0.3.0)

Answer 1

也许这就是你要找的东西：

library(dplyr)

df <- tibble(group = c(1,1,1,1,2,2,2,3,3,3,3,3),
             name = c('Jim','Deb','Bill','Ann','Joe','Jon','Jane','Jake','Sam','Gus','Trixy','Don'),
             type = c(1,2,3,4,3,2,1,2,3,1,4,5))

df %>% 
  group_by(group) %>%
  mutate(new_col = name, name = first(name, order_by = type), type = first(type, order_by = type)) %>% 
  group_by(name, type, .add = TRUE) %>% 
  summarise(new_col = paste(new_col, collapse = ","))
#> `summarise()` regrouping output by 'group', 'name' (override with `.groups` argument)
#> # A tibble: 3 x 4
#> # Groups:   group, name [3]
#>   group name   type new_col               
#>   <dbl> <chr> <dbl> <chr>                 
#> 1     1 Jim       1 Jim,Deb,Bill,Ann      
#> 2     2 Jane      1 Joe,Jon,Jane          
#> 3     3 Gus       1 Jake,Sam,Gus,Trixy,Don

编辑如果new_col 应该是向量列表，那么您可以执行 `summarise(new_col = list(c(new_col)))

df %>% 
  group_by(group) %>%
  mutate(new_col = name, name = first(name, order_by = type), type = first(type, order_by = type)) %>% 
  group_by(name, type, .add = TRUE) %>% 
  summarise(new_col = list(c(new_col)))

另一种选择是使用tidyr::nest：

df %>% 
  group_by(group) %>%
  mutate(new_col = name, name = first(name, order_by = type), type = first(type, order_by = type)) %>% 
  nest(new_col = new_col)