R 折叠行（如果在同一组中）

大家好，我有一个数据帧，例如：

  Group       family
1     A      Canidae
2     B      Canidae
3     A      Felidae
4     B      Canidae
5     C Elephantidae
6     C    Galinacae
7     D    Galinacae
8     D     Siuridae
9     E       Apidae

我想折叠

组

存在

家族

的组（例如：

犬科存在于A和B 因此，我将每个组的所有唯一值合并并添加到

family2

中

Group family2
A,B   Canidae,Felidae 

然后我继续，我看到象甲科和加利那科都在

C

中，thta加利那科也在

D

中，所以我崩溃了：

Group family2
A,B   Canidae,Felidae 
C,D   Elephantidae,Galinacae,Siuridae 

最后，我们应该得到：

Group family2
A,B   Canidae,Felidae 
C,D   Elephantidae,Galinacae,Siuridae 
E     Apidae 

有人有主意吗

这里是为了一个像这样的东西的数据请？非常感谢您的帮助和时间

以下是数据（如果有帮助）：

structure(list(Group = structure(c(1L, 2L, 1L, 2L, 3L, 3L, 4L, 
4L, 5L), .Label = c("A", "B", "C", "D", "E"), class = "factor"), 
    family = structure(c(2L, 2L, 4L, 2L, 3L, 5L, 5L, 6L, 1L), .Label = c("Apidae", 
    "Canidae", "Elephantidae", "Felidae", "Galinacae", "Siuridae"
    ), class = "factor")), class = "data.frame", row.names = c(NA, 
-9L))

---

这是我的解决方案，其中包含一些查找函数

# A lookup function that look for intersect between group 
# if there are at least one intersect - those group will be combined
look_up_group <- function(one_group, lookup_list) {
  matched_list <- map(lookup_list, function(x) {
    tryCatch(
      {
        intersect(x, one_group)
      }, error = function(e) {
        stop(paste0("Error in lookup function: one_group=", one_group, "; x=", x))
      }) 
  })
  
  index <- which(unlist(map(matched_list, function(x) { length(x) > 0 })))
  sort(unique(unlist(lookup_list[index])))
}


df %>%
  # First remove all duplicated rows - exactly the same for both Group, Family
  filter(!duplicated(.)) %>%
  # arrange in alphabetical order
  arrange(Group, family) %>%
  # create a Group_2 which is combination of all Group for each family
  group_by(family) %>%
  mutate(Group_2 = list(Group)) %>%
  ungroup() %>%
  # Create Group_3 which is the full combined Group for all intersect Group
  mutate(Group_3 = map(.[["Group_2"]], function(x) { look_up_group(one_group = x, lookup_list = .[["Group_2"]]) })) %>%
  # Combine all Group_3 into a Group_final
  mutate(Group_final = unlist(map(Group_3, function(x) { paste (x, collapse = ",")} ))) %>%
  # Finally put them all together.
  select(Group_final, family) %>%
  group_by(Group_final) %>%
  summarize(family = paste(family, collapse = ","), .groups = "drop")

然后下一步创建组_3并将它们合并到组_final中 最终结果

# A tibble: 3 x 2
  Group_final family                                   
* <chr>       <chr>                                    
1 A,B         Canidae,Felidae,Canidae                  
2 C,D         Elephantidae,Galinacae,Galinacae,Siuridae
3 E           Apidae 

#一个tible:3 x 2
最后一组
*                                            
1 A，B犬科，猫科，犬科
2 C，D象皮动物科，象皮动物科，象皮动物科，象皮动物科，象皮动物科
3.蜜蜂科

---

[更新：为调试添加了tryCatch]

这感觉很熟悉-您最近是否发布（并删除）了类似的问题？；）请参阅和<代码>g=数据帧（d）中的图形<代码>d$m=组件（g）$membership[d$Group]；然后按“m”粘贴折叠非常感谢，它确实起作用了，因为实际上我收到了以下错误消息：“``问题与

mutate（）

input

Group_3

。x无法将类型“closure”强制为类型“character”的向量ℹ 输入

Group_3

为

map（…）

``你知道发生了什么事吗？@chippycentra-不确定没有实际数据-但很明显，你的数据中有一种情况导致函数

intersect出现错误

-我添加了一个tryCatch，只是为了打印出导致错误的函数-你可以更新函数代码并运行它，看看是什么导致了错误吗？

# remove duplicate & create variable Group_2
tmp <- df %>%
  filter(!duplicated(.)) %>%
  arrange(Group, family) %>%
  group_by(family) %>%
  mutate(Group_2 = list(Group)) %>%
  ungroup()

  Group family       Group_2  
  <fct> <fct>        <list>   
1 A     Canidae      <fct [2]>
2 A     Felidae      <fct [1]>
3 B     Canidae      <fct [2]>
4 C     Elephantidae <fct [1]>
5 C     Galinacae    <fct [2]>
6 D     Galinacae    <fct [2]>
7 D     Siuridae     <fct [1]>
8 E     Apidae       <fct [1]>

> tmp$Group_2
[[1]]
[1] A B
Levels: A B C D E

[[2]]
[1] A
Levels: A B C D E

[[3]]
[1] A B
Levels: A B C D E

[[4]]
[1] C
Levels: A B C D E

[[5]]
[1] C D
Levels: A B C D E

[[6]]
[1] C D
Levels: A B C D E

[[7]]
[1] D
Levels: A B C D E

[[8]]
[1] E
Levels: A B C D E

# Create Group_3
tmp <- tmp %>% 
  mutate(Group_3 = map(.[["Group_2"]],
    function(x) { look_up_group(one_group = x, lookup_list = .[["Group_2"]]) })) %>%
  mutate(Group_final = unlist(map(Group_3, function(x) { paste (x, collapse = ",")} )))

# A tibble: 8 x 5
  Group family       Group_2   Group_3   Group_final
  <fct> <fct>        <list>    <list>    <chr>      
1 A     Canidae      <fct [2]> <fct [2]> A,B        
2 A     Felidae      <fct [1]> <fct [2]> A,B        
3 B     Canidae      <fct [2]> <fct [2]> A,B        
4 C     Elephantidae <fct [1]> <fct [2]> C,D        
5 C     Galinacae    <fct [2]> <fct [2]> C,D        
6 D     Galinacae    <fct [2]> <fct [2]> C,D        
7 D     Siuridae     <fct [1]> <fct [2]> C,D        
8 E     Apidae       <fct [1]> <fct [1]> E     

tmp %>%
  select(Group_final, family) %>%
  group_by(Group_final) %>%
  summarize(family = paste(family, collapse = ","), .groups = "drop")

# A tibble: 3 x 2
  Group_final family                                   
* <chr>       <chr>                                    
1 A,B         Canidae,Felidae,Canidae                  
2 C,D         Elephantidae,Galinacae,Galinacae,Siuridae
3 E           Apidae