这个问题在这里已经有了答案:
Reshaping multiple sets of measurement columns (wide format) into single columns (long format)
(7 个回答)
4年前关闭。
我的数据集如下所示:
unique.id abx.1 start.1 stop.1 abx.2 start.2 stop.2 abx.3 start.3 stop.3 abx.4 start.4
1 1 Moxi 2014-01-01 2014-01-07 PenG 2014-01-01 2014-01-07 Vanco 2014-01-01 2014-01-07 Moxi 2014-01-01
2 2 Moxi 2014-01-01 2014-01-02 Cipro 2014-01-01 2014-01-02 PenG 2014-01-01 2014-01-02 Vanco 2014-01-01
3 3 Cipro 2014-01-01 2014-01-05 Vanco 2014-01-01 2014-01-05 Cipro 2014-01-01 2014-01-05 Vanco 2014-01-01
4 4 Vanco 2014-01-02 2014-01-03 Cipro 2014-01-02 2014-01-03 Cipro 2014-01-02 2014-01-03 PenG 2014-01-02
5 5 Vanco 2014-01-01 2014-01-02 PenG 2014-01-01 2014-01-02 PenG 2014-01-01 2014-01-02 Cipro 2014-01-01
stop.4 intervention
1 2014-01-07 0
2 2014-01-02 0
3 2014-01-05 1
4 2014-01-03 1
5 2014-01-02 0
用一些代码来创建这个:
abxoptions <- c("Cipro", "Moxi", "PenG", "Vanco")
df3 <- data.frame(
unique.id = 1:5,
abx.1 = sample(abxoptions,5, replace=TRUE),
start.1 = as.Date(c('2014-01-01', '2014-01-01', '2014-01-01', '2014-01-02', '2014-01-01')),
stop.1 = as.Date(c('2014-01-07', '2014-01-02', '2014-01-05', '2014-01-03', '2014-01-02')),
abx.2 = sample(abxoptions,5, replace=TRUE),
start.2 = as.Date(c('2014-01-01', '2014-01-01', '2014-01-01', '2014-01-02', '2014-01-01')),
stop.2 = as.Date(c('2014-01-07', '2014-01-02', '2014-01-05', '2014-01-03', '2014-01-02')),
abx.3 = sample(abxoptions,5, replace=TRUE),
start.3 = as.Date(c('2014-01-01', '2014-01-01', '2014-01-01', '2014-01-02', '2014-01-01')),
stop.3 = as.Date(c('2014-01-07', '2014-01-02', '2014-01-05', '2014-01-03', '2014-01-02')),
abx.4 = sample(abxoptions,5, replace=TRUE),
start.4 = as.Date(c('2014-01-01', '2014-01-01', '2014-01-01', '2014-01-02', '2014-01-01')),
stop.4 = as.Date(c('2014-01-07', '2014-01-02', '2014-01-05', '2014-01-03', '2014-01-02')),
intervention = c(0,0,1,1,0)
)
我想整理这些数据看起来像这样:
unique.id abx start stop intervention
1 Moxi 2014-01-10 2014-01-07 0
1 Pen G 2014-01-01 2014-01-07 0
1 Vanco 2014-01-01 2014-01-07 0
1 Moxi 2014-01-01 2014-01-07 0 etc etc
以下解决方案没有让我到达我需要的地方:
Gather multiple sets of columns和
Combining multiple columns into one
我怀疑 Hadley 令人惊叹的 tidyr pakcage 是要走的路……只是想不通。任何帮助将不胜感激。
最佳答案
几乎所有的数据整理问题都可以通过三个步骤来解决:
(通常您只需要其中的一两个,但我认为它们几乎总是按此顺序排列)。
对于您的数据:
unique.id
这看起来像:
library(tidyr)
library(dplyr)
df3 %>%
gather(col, value, -unique.id, -intervention) %>%
separate(col, c("variable", "number")) %>%
spread(variable, value, convert = TRUE) %>%
mutate(start = as.Date(start, "1970-01-01"), stop = as.Date(stop, "1970-01-01"))
你的情况有点复杂,因为你有两种类型的变量,所以你需要在最后恢复这些类型。
关于r - 将多列组合成整洁的数据,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/28729506/