我有一个包含超过300列和行的数据集，如下所示：
old= data.frame(
id=1:3,
DATE=c('20/12/1965','11/101970','03/12/1985'),
TRT=c(1,2,1),
AT1=c(40,89,50),
AT2=c(18,43,13),
AT3=c(23,16,10),
BECT1=c(80,50,60),
BECT2=c(78,40,48),
BECT3=c(60,97,56),
C0T1=c(43,45,78),
C0T2=c(42,NA,48))
我想将我的数据转换为如下所示：
new=data.frame(ID=c(1,1,1,2,2,2,3,3,3),
TRT=c(1,1,1,2,2,2,1,1,1),
DATE=c('20/12/1965','20/12/1965','20/12/1965','11/10/1970','11/10/1970','11/10/1970','03/12/1985','03/12/1985','03/12/1985'),
variable1=c('ATI','AT2','AT3','ATI','AT2','AT3','ATI','AT2','AT3'),
value1=c(20,23,18,89,43,16,50,13,10),
variable2=c('BECT1','BECT2','BECT3','BECT1','BECT2','BECT3','BECT1','BECT2','BECT3'),
value2=c(80,78,60,50,40,97,60,48,56),
Variable3= c('C0T1','C0T2','C0T3','C0T1','C0T2','C0T3','C0T1','C0T2','C0T3'),
value3=c(43,42,85,45,63,NA,78,48,48))
感谢
答案 0 :(得分：2)
您可以使用gather包中的tidyr，并从dplyr安排：
library(dplyr)
library(tidyr)
old_df= data.frame(
id=1:3,
DATE=c('20/12/1965','11/10/1970','03/12/1985'),
TRT=c(1,2,1),
AT1=c(40,89,50),
AT2=c(18,43,13),
AT3=c(23,16,10),
BECT1=c(80,50,60),
BECT2=c(78,40,48),
BECT3=c(60,97,56),
C0T1=c(43,45,78),
C0T2=c(42,NA,48))
new_df <- old_df %>%
gather(AT1, AT2, AT3, key = "variable1", value = "value1") %>%
gather(BECT1, BECT2, BECT3, key = "variable2", value = "value2") %>%
gather(C0T1, C0T2, key = "variable3", value = "value3") %>%
arrange(id, DATE, TRT, variable1, variable2, variable3)
id DATE TRT variable1 value1 variable2 value2 variable3 value3
1 1 20/12/1965 1 AT1 40 BECT1 80 C0T1 43
2 1 20/12/1965 1 AT1 40 BECT1 80 C0T2 42
3 1 20/12/1965 1 AT1 40 BECT2 78 C0T1 43
4 1 20/12/1965 1 AT1 40 BECT2 78 C0T2 42
5 1 20/12/1965 1 AT1 40 BECT3 60 C0T1 43
6 1 20/12/1965 1 AT1 40 BECT3 60 C0T2 42
7 1 20/12/1965 1 AT2 18 BECT1 80 C0T1 43
8 1 20/12/1965 1 AT2 18 BECT1 80 C0T2 42
9 1 20/12/1965 1 AT2 18 BECT2 78 C0T1 43
10 1 20/12/1965 1 AT2 18 BECT2 78 C0T2 42
11 1 20/12/1965 1 AT2 18 BECT3 60 C0T1 43
12 1 20/12/1965 1 AT2 18 BECT3 60 C0T2 42
13 1 20/12/1965 1 AT3 23 BECT1 80 C0T1 43
14 1 20/12/1965 1 AT3 23 BECT1 80 C0T2 42
15 1 20/12/1965 1 AT3 23 BECT2 78 C0T1 43
16 1 20/12/1965 1 AT3 23 BECT2 78 C0T2 42
17 1 20/12/1965 1 AT3 23 BECT3 60 C0T1 43
18 1 20/12/1965 1 AT3 23 BECT3 60 C0T2 42
19 2 11/10/1970 2 AT1 89 BECT1 50 C0T1 45
20 2 11/10/1970 2 AT1 89 BECT1 50 C0T2 NA
21 2 11/10/1970 2 AT1 89 BECT2 40 C0T1 45
22 2 11/10/1970 2 AT1 89 BECT2 40 C0T2 NA
23 2 11/10/1970 2 AT1 89 BECT3 97 C0T1 45
24 2 11/10/1970 2 AT1 89 BECT3 97 C0T2 NA
25 2 11/10/1970 2 AT2 43 BECT1 50 C0T1 45
26 2 11/10/1970 2 AT2 43 BECT1 50 C0T2 NA
27 2 11/10/1970 2 AT2 43 BECT2 40 C0T1 45
28 2 11/10/1970 2 AT2 43 BECT2 40 C0T2 NA
29 2 11/10/1970 2 AT2 43 BECT3 97 C0T1 45
30 2 11/10/1970 2 AT2 43 BECT3 97 C0T2 NA
31 2 11/10/1970 2 AT3 16 BECT1 50 C0T1 45
32 2 11/10/1970 2 AT3 16 BECT1 50 C0T2 NA
33 2 11/10/1970 2 AT3 16 BECT2 40 C0T1 45
34 2 11/10/1970 2 AT3 16 BECT2 40 C0T2 NA
35 2 11/10/1970 2 AT3 16 BECT3 97 C0T1 45
36 2 11/10/1970 2 AT3 16 BECT3 97 C0T2 NA
37 3 03/12/1985 1 AT1 50 BECT1 60 C0T1 78
38 3 03/12/1985 1 AT1 50 BECT1 60 C0T2 48
39 3 03/12/1985 1 AT1 50 BECT2 48 C0T1 78
40 3 03/12/1985 1 AT1 50 BECT2 48 C0T2 48
41 3 03/12/1985 1 AT1 50 BECT3 56 C0T1 78
42 3 03/12/1985 1 AT1 50 BECT3 56 C0T2 48
43 3 03/12/1985 1 AT2 13 BECT1 60 C0T1 78
44 3 03/12/1985 1 AT2 13 BECT1 60 C0T2 48
45 3 03/12/1985 1 AT2 13 BECT2 48 C0T1 78
46 3 03/12/1985 1 AT2 13 BECT2 48 C0T2 48
47 3 03/12/1985 1 AT2 13 BECT3 56 C0T1 78
48 3 03/12/1985 1 AT2 13 BECT3 56 C0T2 48
49 3 03/12/1985 1 AT3 10 BECT1 60 C0T1 78
50 3 03/12/1985 1 AT3 10 BECT1 60 C0T2 48
51 3 03/12/1985 1 AT3 10 BECT2 48 C0T1 78
52 3 03/12/1985 1 AT3 10 BECT2 48 C0T2 48
53 3 03/12/1985 1 AT3 10 BECT3 56 C0T1 78
54 3 03/12/1985 1 AT3 10 BECT3 56 C0T2 48
答案 1 :(得分：1)
transposeData <- function(df) {
rowList <- list()
# store each column as a vector in a list
for (i in seq_along(df)) {
rowList[[i]] <- t(df[, i])
}
# combine each component (vector) of the list by row
newDf <- do.call(what = rbind, args = rowList)
newDf <- as.data.frame(newDf)
# gives the names of the columns as rownames in the new data
rownames(newDf) <- names(df)
# name the column of the new data as the observation index
names(newDf) <- paste("obs", 1:dim(df)[1])
newDf
}
输出是一个数据框，其观察结果为列。
>transposeData(old)
obs 1 obs 2 obs 3
id 1 2 3
DATE 3 2 1
TRT 1 2 1
AT1 40 89 50
AT2 18 43 13
AT3 23 16 10
BECT1 80 50 60
BECT2 78 40 48
BECT3 60 97 56
C0T1 43 45 78
C0T2 42 NA 48
DATE 列的问题是在创建数据框时强制作为因素。那么，在for transposeData()函数内部，当列被提取为向量时，您将获得因子级别索引，而不是日期。您可以使用条件if修复此问题。