我真的不知道如何在不使用 for 循环的情况下实现这一目标:
x <- c('a', 'b', 'c', 'd')
> x
[1] "a" "b" "c" "d"
data <- data.frame(
x=c('a', 'b', 'a', 'b', 'c', 'a', 'a', 'b', 'c', 'd'),
name=c('one','one', 'two','two','two', 'three', 'four','four','four','four'),
other=c(1, 4, 5, 3, 2, 4, 5, 6, 3, 2)
)
> data
x name other
1 a one 1
2 b one 4
3 a two 5
4 b two 3
5 c two 2
6 a three 4
7 a four 5
8 b four 6
9 c four 3
10 d four 2
我愿意分data
通过价值name
and merge
每个子群都有x
填充“缺失的行”,得到如下内容:
> data
x name other
1 a one 1
2 b one 4
c one 0 <- missing row added
d one 0 <- missing row added
3 a two 5
4 b two 3
5 c two 2
d two 0 <- missing row added
6 a three 4
b three 0 <- missing row added
c three 0 <- missing row added
d three 0 <- missing row added
7 a four 5
8 b four 6
9 c four 3
10 d four 2
最后,重新格式化data.frame
像这样:
> data
x one two three four
1 a 1 5 4 5
2 b 4 3 0 6
3 c 0 2 0 3
4 d 0 0 0 2
我可以使用 for 循环来实现它,但我确信必须有更好的解决方案*apply
, by
, split
或类似的东西。有什么建议么?
** 更新 **
我最终对已接受的答案进行了一些修改(再次强调,伙计!),因为我不太喜欢与levels
我不关心列的顺序:
grid <- expand.grid(x, unique(data$name))
colnames(grid) <- c("x", "name")
data <- merge(grid, data, all.x = TRUE)
data[is.na(data)] <- 0
dcast(data, x ~ name, value.var = 'other')