具有多个变量和 ID R 的从宽到长的数据框 [英] Data frame from wide to long with multiple variables and ids R

问题描述

我有一个数据框，其中包含参与者对两个文本的判断.假设每个文本都有一个正确答案和一个标识符，并且每个文本都被判断多次.

I have a dataframe with participants' judgments for two texts. Suppose each text has a correct answer and an identifier, and each text is judged multple times.

set.seed(123)
wide_df = data.frame('participant_id' = LETTERS[1:12]
                 , 'judgment_1' = round(rnorm(12)*100)
                 , 'correct_1' = round(rnorm(12)*100)
                 , 'text_id_1' = sample(1:12, 12, replace = F)
                 , 'judgment_2' = round(rnorm(12)*100)
                 , 'correct_2' = round(rnorm(12)*100)
                 , 'text_id_2' = sample(13:24, 12, replace = F)
                 )

所以:

   participant_id judgment_1 correct_1 text_id_1 judgment_2 correct_2 text_id_2
1               A        -56        40         4         43      -127        17
2               B        -23        11        10        -30       217        14
3               C        156       -56         1         90       121        22
4               D          7       179        12         88      -112        15
5               E         13        50         7         82       -40        13
...

我想将其转换为带有列的长格式:

I would want to convert this to the long format with the columns:

participant_id   text_id   judgment   correct
             A         4        -56        40
             A        17         43       127     
...

我在此处找到并遵循了 SO 建议:

I found and followed the SO advice here:

wide_df %>% 
  gather(v, value, judgment_1:text_id_2) %>% 
  separate(v, c("var", "col")) %>% 
  arrange(participant_id) %>% 
  spread(col, value)

但是这种重塑方式会返回错误 Error: Duplicate identifiers for rows (3, 6), (9, 12)

But that way of reshaping returns the error Error: Duplicate identifiers for rows (3, 6), (9, 12)

我认为我在概念上做错了但无法完全找到它.我的错误在哪里?谢谢！

I think I do something conceptually wrong but can't quite find it. Where is my mistake? Thanks!

推荐答案

这里已经有了答案:https://stackoverflow.com/a/12466668/2371031

例如，

set.seed(123)
wide_df = data.frame('participant_id' = LETTERS[1:12]
                     , 'judgment_1' = round(rnorm(12)*100)
                     , 'correct_1' = round(rnorm(12)*100)
                     , 'text_id_1' = sample(1:12, 12, replace = F)
                     , 'judgment_2' = round(rnorm(12)*100)
                     , 'correct_2' = round(rnorm(12)*100)
                     , 'text_id_2' = sample(13:24, 12, replace = F)
)

dl <- reshape(data = wide_df, 
              idvar = "participant_id", 
              varying = list(judgment=c(2,5),correct=c(3,6),text_id=c(4,7)), 
              direction="long", 
              v.names = c("judgment","correct","text_id"),
              sep="_")

结果:

    participant_id time judgment correct text_id
A.1              A    1      -56      40       4
B.1              B    1      -23      11      10
C.1              C    1      156     -56       1
D.1              D    1        7     179      12
E.1              E    1       13      50       7
F.1              F    1      172    -197      11
G.1              G    1       46      70       9
H.1              H    1     -127     -47       2
I.1              I    1      -69    -107       8
J.1              J    1      -45     -22       3
K.1              K    1      122    -103       5
L.1              L    1       36     -73       6
A.2              A    2       43    -127      17
B.2              B    2      -30     217      14
C.2              C    2       90     121      22
D.2              D    2       88    -112      15
E.2              E    2       82     -40      13
F.2              F    2       69     -47      19
G.2              G    2       55      78      24
H.2              H    2       -6      -8      20
I.2              I    2      -31      25      21
J.2              J    2      -38      -3      16
K.2              K    2      -69      -4      23
L.2              L    2      -21     137      18

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