r - 如何通过分解包含 r 中向量的列来拉伸(stretch)数据框？

Question

我有一个数据框，其中有一列包含向量作为值。现在我需要通过分解向量来拉伸(stretch)这个数据框。

看看这个例子:

df <- structure(list(id = c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2), id2 = c(1, 
2, 3, 4, 5, 1, 2, 3, 4, 5), value = c("1", "2", "3", "c(1,3,4)", 
"1:5", "1", "2", "3", "1:4", "2:4")), .Names = c("id", "id2", 
"value"), row.names = c(NA, 10L), class = "data.frame")
df
   id id2    value
1   1   1        1
2   1   2        2
3   1   3        3
4   1   4 c(1,3,4)
5   1   5      1:5
6   2   1        1
7   2   2        2
8   2   3        3
9   2   4      1:4
10  2   5      2:4

this has to be changed into:

df2 <- structure(list(id = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), id2 = c(1L, 2L, 
3L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 1L, 2L, 3L, 4L, 4L, 4L, 4L, 
5L, 5L, 5L), value = c(1L, 2L, 3L, 1L, 3L, 4L, 1L, 2L, 3L, 4L, 
5L, 1L, 2L, 3L, 1L, 2L, 3L, 4L, 2L, 3L, 4L)), .Names = c("id", 
"id2", "value"), class = "data.frame", row.names = c(NA, -21L
))

df2
   id id2 value
1   1   1     1
2   1   2     2
3   1   3     3
4   1   4     1
5   1   4     3
6   1   4     4
7   1   5     1
8   1   5     2
9   1   5     3
10  1   5     4
11  1   5     5
12  2   1     1
13  2   2     2
14  2   3     3
15  2   4     1
16  2   4     2
17  2   4     3
18  2   4     4
19  2   5     2
20  2   5     3
21  2   5     4

因此，将宽格式转换为长格式是一种不同于我们习惯的函数，例如reshape2 包。有人能解决这个问题吗？

*编辑

我忘了说有些值实际上是像这样的字符值:

df <- structure(list(id = c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2), id2 = c(1, 
2, 3, 4, 5, 1, 2, 3, 4, 5), value = c("1", "2", "Hi", "c(1,3,4)", 
"1:5", "1", "2", "hello", "1:4", "2:4")), .Names = c("id", "id2", 
"value"), row.names = c(NA, 10L), class = "data.frame")
df
   id id2    value
1   1   1        1
2   1   2        2
3   1   3       Hi
4   1   4 c(1,3,4)
5   1   5      1:5
6   2   1        1
7   2   2        2
8   2   3    hello
9   2   4      1:4
10  2   5      2:4

Answer 1

类似地，使用 data.table

的一行

library(data.table)
setDT(df)[, as.integer(eval.parent(parse(text = value))), by = .(id, id2)]
#     id id2 V1
#  1:  1   1  1
#  2:  1   2  2
#  3:  1   3  3
#  4:  1   4  1
#  5:  1   4  3
#  6:  1   4  4
#  7:  1   5  1
#  8:  1   5  2
#  9:  1   5  3
# 10:  1   5  4
# 11:  1   5  5
# 12:  2   1  1
# 13:  2   2  2
# 14:  2   3  3
# 15:  2   4  1
# 16:  2   4  2
# 17:  2   4  3
# 18:  2   4  4
# 19:  2   5  2
# 20:  2   5  3
# 21:  2   5  4