R：将宽数据帧转换为超过两列的纵向格式
R: To convert wide dataframe into longitudinal format with more than more than two columns
我有如下数据框：
> head(n)
# A tibble: 6 x 23
`Record ID of REGN DATA` Pain_1 Pain_2 Redness_1 Redness_2 Swelling_1 Swelling_2
<dbl> <chr> <chr> <chr> <chr> <chr> <chr>
1 1 Yes Yes No No No No
2 2 No Yes No No No No
3 3 Yes No No No No No
4 4 Yes Yes No No Yes Yes
5 5 No No No No No No
6 6 No No No No No No
Pain_1和Pain_2分别是患者第一次就诊和第二次就诊时症状“疼痛”的答案。变量Redness和Swelling也是如此。我想将数据框转换为每个症状的纵向数据框 Pain、Redness 和 Swelling 以及一个标志变量以显示访问次数，如下所示。我尝试使用 gather 函数将所有症状转换为一列。有好心人帮忙吗
> head(tr)
# A tibble: 6 x 5
`Record ID of REGN DATA` Pain Redness Swelling Visit
<dbl> <chr> <chr> <chr> <dbl>
1 1 Yes No No 1
2 2 No No No 1
3 3 Yes No No 1
4 1 Yes No No 2
5 2 Yes No No 2
6 3 No No No 2
这是示例数据
structure(list(`Record ID of REGN DATA` = c(1, 2, 3, 4, 5, 6,
7, 8, 9, 10), Pain_1 = c("Yes", "No", "Yes", "Yes", "No", "No",
"Yes", "Yes", "Yes", "Yes"), Pain_2 = c("Yes", "Yes", "No", "Yes",
"No", "No", "No", "Yes", "Yes", "Yes"), Redness_1 = c("No", "No",
"No", "No", "No", "No", "Yes", "Yes", "No", "No"), Redness_2 = c("No",
"No", "No", "No", "No", "No", "No", "Yes", "No", "No"), Swelling_1 = c("No",
"No", "No", "Yes", "No", "No", "No", "Yes", "No", "Yes"), Swelling_2 = c("No",
"No", "No", "Yes", "No", "No", "No", "Yes", "No", "Yes"), Tiredness_1 = c("Yes",
"No", "Yes", "Yes", "No", "No", "No", "No", "No", "Yes"), Tiredness_2 = c("Yes",
"Yes", "No", "Yes", "No", "No", "Yes", "No", "Yes", "Yes"), Headache_1 = c("No",
"No", "No", "Yes", "No", "No", "No", "No", "No", "No"), Headache_2 = c("No",
"Yes", "No", "Yes", "No", "No", "No", "Yes", "No", "No"), Muscle_1 = c("Yes",
"No", "Yes", "Yes", "No", "No", "No", "No", "No", "No"), Muscle_2 = c("Yes",
"Yes", "No", "No", "No", "No", "Yes", "Yes", "No", "No"), Chills_1 = c("No",
"No", "Yes", "No", "No", "No", "No", "No", "No", "No"), Chills_2 = c("No",
"Yes", "No", "No", "No", "No", "Yes", "No", "No", "No"), Fever_1 = c("Yes",
"No", "No", "No", "No", "No", "No", "No", "Yes", "Yes"), Fever_2 = c("Yes",
"Yes", "No", "No", "No", "No", "Yes", "No", "No", "No"), Nausea_1 = c("No",
"No", "No", "No", "No", "No", "No", "No", "No", "No"), Nausea_2 = c("No",
"No", "No", "No", "No", "No", "No", "Yes", "No", "No"), JointPain_1 = c("Yes",
"No", "Yes", "No", "No", "No", "No", "No", "Yes", "No"), JointPain_2 = c("Yes",
"No", "No", "No", "No", "No", "Yes", "No", "No", "No"), `Allergic reaction_1` = c("No",
"No", "No", "No", "No", "No", "No", "No", "No", "No"), `Allergic reaction_2` = c("No",
"No", "No", "No", "No", "No", "No", "No", "No", "No")), row.names = c(NA,
-10L), class = c("tbl_df", "tbl", "data.frame"))
一种方法是 pivot_longer，然后您可以使用 separate 获取访问次数，然后您可以过滤到感兴趣的变量，然后 pivot_wider 获取到您的预期输出。 （如果我没看错你在找什么）
library(tidyverse)
df %>%
pivot_longer(!`Record ID of REGN DATA`,
names_to = "name",
values_to = "value") %>%
separate(name, c("name", "visit"), sep = "_") %>%
filter(name %in% c("Pain", "Redness", "Swelling")) %>%
pivot_wider(names_from = "name", values_from = "value") %>%
select(1, 3:5, 2)
输出
# A tibble: 20 × 5
`Record ID of REGN DATA` Pain Redness Swelling visit
<dbl> <chr> <chr> <chr> <chr>
1 1 Yes No No 1
2 1 Yes No No 2
3 2 No No No 1
4 2 Yes No No 2
5 3 Yes No No 1
6 3 No No No 2
7 4 Yes No Yes 1
8 4 Yes No Yes 2
9 5 No No No 1
10 5 No No No 2
11 6 No No No 1
12 6 No No No 2
13 7 Yes Yes No 1
14 7 No No No 2
15 8 Yes Yes Yes 1
16 8 Yes Yes Yes 2
17 9 Yes No No 1
18 9 Yes No No 2
19 10 Yes No Yes 1
20 10 Yes No Yes 2
使用 pivot_longer 的 names_sep 参数的更直接的方法：
library(tidyr)
df %>%
pivot_longer(
cols = -1,
names_to = c(".value", "visit"),
names_sep = "_"
)
`Record ID of REG~ visit Pain Redness Swelling Tiredness Headache Muscle Chills Fever Nausea JointPain `Allergic react~
<dbl> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 1 1 Yes No No Yes No Yes No Yes No Yes No
2 1 2 Yes No No Yes No Yes No Yes No Yes No
3 2 1 No No No No No No No No No No No
4 2 2 Yes No No Yes Yes Yes Yes Yes No No No
5 3 1 Yes No No Yes No Yes Yes No No Yes No
6 3 2 No No No No No No No No No No No
7 4 1 Yes No Yes Yes Yes Yes No No No No No
8 4 2 Yes No Yes Yes Yes No No No No No No
9 5 1 No No No No No No No No No No No
10 5 2 No No No No No No No No No No No
11 6 1 No No No No No No No No No No No
12 6 2 No No No No No No No No No No No
13 7 1 Yes Yes No No No No No No No No No
14 7 2 No No No Yes No Yes Yes Yes No Yes No
15 8 1 Yes Yes Yes No No No No No No No No
16 8 2 Yes Yes Yes No Yes Yes No No Yes No No
17 9 1 Yes No No No No No No Yes No Yes No
18 9 2 Yes No No Yes No No No No No No No
19 10 1 Yes No Yes Yes No No No Yes No No No
20 10 2 Yes No Yes Yes No No No No No No No
我有如下数据框：
> head(n)
# A tibble: 6 x 23
`Record ID of REGN DATA` Pain_1 Pain_2 Redness_1 Redness_2 Swelling_1 Swelling_2
<dbl> <chr> <chr> <chr> <chr> <chr> <chr>
1 1 Yes Yes No No No No
2 2 No Yes No No No No
3 3 Yes No No No No No
4 4 Yes Yes No No Yes Yes
5 5 No No No No No No
6 6 No No No No No No
Pain_1和Pain_2分别是患者第一次就诊和第二次就诊时症状“疼痛”的答案。变量Redness和Swelling也是如此。我想将数据框转换为每个症状的纵向数据框 Pain、Redness 和 Swelling 以及一个标志变量以显示访问次数，如下所示。我尝试使用 gather 函数将所有症状转换为一列。有好心人帮忙吗
> head(tr)
# A tibble: 6 x 5
`Record ID of REGN DATA` Pain Redness Swelling Visit
<dbl> <chr> <chr> <chr> <dbl>
1 1 Yes No No 1
2 2 No No No 1
3 3 Yes No No 1
4 1 Yes No No 2
5 2 Yes No No 2
6 3 No No No 2
这是示例数据
structure(list(`Record ID of REGN DATA` = c(1, 2, 3, 4, 5, 6,
7, 8, 9, 10), Pain_1 = c("Yes", "No", "Yes", "Yes", "No", "No",
"Yes", "Yes", "Yes", "Yes"), Pain_2 = c("Yes", "Yes", "No", "Yes",
"No", "No", "No", "Yes", "Yes", "Yes"), Redness_1 = c("No", "No",
"No", "No", "No", "No", "Yes", "Yes", "No", "No"), Redness_2 = c("No",
"No", "No", "No", "No", "No", "No", "Yes", "No", "No"), Swelling_1 = c("No",
"No", "No", "Yes", "No", "No", "No", "Yes", "No", "Yes"), Swelling_2 = c("No",
"No", "No", "Yes", "No", "No", "No", "Yes", "No", "Yes"), Tiredness_1 = c("Yes",
"No", "Yes", "Yes", "No", "No", "No", "No", "No", "Yes"), Tiredness_2 = c("Yes",
"Yes", "No", "Yes", "No", "No", "Yes", "No", "Yes", "Yes"), Headache_1 = c("No",
"No", "No", "Yes", "No", "No", "No", "No", "No", "No"), Headache_2 = c("No",
"Yes", "No", "Yes", "No", "No", "No", "Yes", "No", "No"), Muscle_1 = c("Yes",
"No", "Yes", "Yes", "No", "No", "No", "No", "No", "No"), Muscle_2 = c("Yes",
"Yes", "No", "No", "No", "No", "Yes", "Yes", "No", "No"), Chills_1 = c("No",
"No", "Yes", "No", "No", "No", "No", "No", "No", "No"), Chills_2 = c("No",
"Yes", "No", "No", "No", "No", "Yes", "No", "No", "No"), Fever_1 = c("Yes",
"No", "No", "No", "No", "No", "No", "No", "Yes", "Yes"), Fever_2 = c("Yes",
"Yes", "No", "No", "No", "No", "Yes", "No", "No", "No"), Nausea_1 = c("No",
"No", "No", "No", "No", "No", "No", "No", "No", "No"), Nausea_2 = c("No",
"No", "No", "No", "No", "No", "No", "Yes", "No", "No"), JointPain_1 = c("Yes",
"No", "Yes", "No", "No", "No", "No", "No", "Yes", "No"), JointPain_2 = c("Yes",
"No", "No", "No", "No", "No", "Yes", "No", "No", "No"), `Allergic reaction_1` = c("No",
"No", "No", "No", "No", "No", "No", "No", "No", "No"), `Allergic reaction_2` = c("No",
"No", "No", "No", "No", "No", "No", "No", "No", "No")), row.names = c(NA,
-10L), class = c("tbl_df", "tbl", "data.frame"))
一种方法是 pivot_longer，然后您可以使用 separate 获取访问次数，然后您可以过滤到感兴趣的变量，然后 pivot_wider 获取到您的预期输出。 （如果我没看错你在找什么）
library(tidyverse)
df %>%
pivot_longer(!`Record ID of REGN DATA`,
names_to = "name",
values_to = "value") %>%
separate(name, c("name", "visit"), sep = "_") %>%
filter(name %in% c("Pain", "Redness", "Swelling")) %>%
pivot_wider(names_from = "name", values_from = "value") %>%
select(1, 3:5, 2)
输出
# A tibble: 20 × 5
`Record ID of REGN DATA` Pain Redness Swelling visit
<dbl> <chr> <chr> <chr> <chr>
1 1 Yes No No 1
2 1 Yes No No 2
3 2 No No No 1
4 2 Yes No No 2
5 3 Yes No No 1
6 3 No No No 2
7 4 Yes No Yes 1
8 4 Yes No Yes 2
9 5 No No No 1
10 5 No No No 2
11 6 No No No 1
12 6 No No No 2
13 7 Yes Yes No 1
14 7 No No No 2
15 8 Yes Yes Yes 1
16 8 Yes Yes Yes 2
17 9 Yes No No 1
18 9 Yes No No 2
19 10 Yes No Yes 1
20 10 Yes No Yes 2
使用 pivot_longer 的 names_sep 参数的更直接的方法：
library(tidyr)
df %>%
pivot_longer(
cols = -1,
names_to = c(".value", "visit"),
names_sep = "_"
)
`Record ID of REG~ visit Pain Redness Swelling Tiredness Headache Muscle Chills Fever Nausea JointPain `Allergic react~
<dbl> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 1 1 Yes No No Yes No Yes No Yes No Yes No
2 1 2 Yes No No Yes No Yes No Yes No Yes No
3 2 1 No No No No No No No No No No No
4 2 2 Yes No No Yes Yes Yes Yes Yes No No No
5 3 1 Yes No No Yes No Yes Yes No No Yes No
6 3 2 No No No No No No No No No No No
7 4 1 Yes No Yes Yes Yes Yes No No No No No
8 4 2 Yes No Yes Yes Yes No No No No No No
9 5 1 No No No No No No No No No No No
10 5 2 No No No No No No No No No No No
11 6 1 No No No No No No No No No No No
12 6 2 No No No No No No No No No No No
13 7 1 Yes Yes No No No No No No No No No
14 7 2 No No No Yes No Yes Yes Yes No Yes No
15 8 1 Yes Yes Yes No No No No No No No No
16 8 2 Yes Yes Yes No Yes Yes No No Yes No No
17 9 1 Yes No No No No No No Yes No Yes No
18 9 2 Yes No No Yes No No No No No No No
19 10 1 Yes No Yes Yes No No No Yes No No No
20 10 2 Yes No Yes Yes No No No No No No No