r - 使用存储在行 R 中的 key 将数据帧从宽格式转换为长格式

Question

我正在使用 tidyverse 但也欢迎使用 base 解决方案。

有没有一种方法可以在不转置的情况下收集数据框，而不是key作为列名，key被存储连续。例如，假设我有一个名为 df 的小标题。

df <- tibble(a = c(5,3,5,6,2,"G1"),
             b = c(5,3,5,6,2,"G1"),
             c = c(8,2,6,4,1,"G2"),
             d = c(8,2,6,4,1,"G2"),
             e = c(9,3,7,8,4,"G3"),
             f = c(9,3,7,8,4,"G3"),
             g = c(6,5,2,1,8,"G4"),
             h = c(6,5,2,1,8,"G4"))
df
# A tibble: 6 x 8
  a     b     c     d     e     f     g     h    
  <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 5     5     8     8     9     9     6     6    
2 3     3     2     2     3     3     5     5    
3 5     5     6     6     7     7     2     2    
4 6     6     4     4     8     8     1     1    
5 2     2     1     1     4     4     8     8    
6 G1    G1    G2    G2    G3    G3    G4    G4 

要分组或聚集的组位于底行。有没有办法让 df 只有三列，这样 c、e 和 g 列聚集到 a 列中，d、f 和 h 列聚集到 b 列和行中6 变成 c 列？结果看起来像:

tibble(a = c(5,3,5,6,2,8,2,6,4,1,9,3,7,8,4,6,5,2,1,8),
       b = c(5,3,5,6,2,8,2,6,4,1,9,3,7,8,4,6,5,2,1,8),
       c = c("G1","G1","G1","G1","G1","G2","G2","G2","G2","G2",
             "G3","G3","G3","G3","G3","G4","G4","G4","G4","G4"))
# A tibble: 20 x 3
       a     b c    
   <dbl> <dbl> <chr>
 1     5     5 G1   
 2     3     3 G1   
 3     5     5 G1   
 4     6     6 G1   
 5     2     2 G1   
 6     8     8 G2   
 7     2     2 G2   
 8     6     6 G2   
 9     4     4 G2   
10     1     1 G2   
11     9     9 G3   
12     3     3 G3   
13     7     7 G3   
14     8     8 G3   
15     4     4 G3   
16     6     6 G4   
17     5     5 G4   
18     2     2 G4   
19     1     1 G4   
20     8     8 G4 

我想避免转置，因为我需要保留行和列的顺序，直到所有内容都被正确标记为止。

Answer 1

这是一个想法。

library(tidyverse)

df2 <- df %>%
  t() %>%
  as.data.frame(stringsAsFactors = FALSE) %>%
  split(f = .$V6) %>%
  map_dfr(~.x %>% 
            select(-V6) %>%
            t() %>%
            as.data.frame(stringsAsFactors = FALSE) %>%
            setNames(c("a", "b")),
          .id = "c") %>%
  select(a, b, c) %>%
  mutate_at(vars(-c), list(~as.numeric(.)))

df2
#    a b  c
# 1  5 5 G1
# 2  3 3 G1
# 3  5 5 G1
# 4  6 6 G1
# 5  2 2 G1
# 6  8 8 G2
# 7  2 2 G2
# 8  6 6 G2
# 9  4 4 G2
# 10 1 1 G2
# 11 9 9 G3
# 12 3 3 G3
# 13 7 7 G3
# 14 8 8 G3
# 15 4 4 G3
# 16 6 6 G4
# 17 5 5 G4
# 18 2 2 G4
# 19 1 1 G4
# 20 8 8 G4