Question

这是Stata在一步中处理的数据分析中的基本问题。

使用时间不变数据（x0）和2000年和2005年的时变数据（x1，x2）创建一个宽数据框：

d1 <- data.frame(subject = c("id1", "id2"),  
x0 = c("male", "female"),  
x1_2000 = 1:2,   
x1_2005 = 5:6,  
x2_2000 = 1:2,  
x2_2005 = 5:6    
)

s.t。

subject x0 x1_2000 x1_2005 x2_2000 x2_2005  
1     id1 male         1       5       1       5  
2     id2 female       2       6       2       6

我想像面板一样塑造它，所以数据看起来像这样：

        subject     x0 time x1 x2
1     id1   male 2000  1  1
2     id2 female 2000  2  2
3     id1   male 2005  5  5
4     id2 female 2005  6  6

我可以使用reshape s.t。

执行此操作

d2 <-reshape(d1, 
idvar="subject",
varying=list(c("x1_2000","x1_2005"),
    c("x2_2000","x2_2005")),
    v.names=c("x1","x2"),
    times = c(2000,2005),
    direction = "long",
    sep= "_")

我主要担心的是，当你有几十个变量时，上面的命令会变得很长。在stata中，只需键入：

reshape long x1 x2, i(subject) j(year)

R中有这么简单的解决方案吗？

Answer 1

reshape可以猜出它的许多论点。在这种情况下，指定以下内容就足够了。没有包使用。

 reshape(d1, dir = "long", varying = 3:6, sep = "_")

，并提供：

       subject     x0 time x1 x2 id
1.2000     id1   male 2000  1  1  1
2.2000     id2 female 2000  2  2  2
1.2005     id1   male 2005  5  5  1
2.2005     id2 female 2005  6  6  2

Answer 2

这是使用reshape2包的简短示例：

library(reshape2)
library(stringr)

# it is always useful to start with melt
d2 <- melt(d1, id=c("subject", "x0"))

# redefine the time and x1, x2, ... separately
d2 <- transform(d2, time = str_replace(variable, "^.*_", ""),
                    variable = str_replace(variable, "_.*$", ""))

# finally, cast as you want
d3 <- dcast(d2, subject+x0+time~variable)

现在你甚至不需要指定x1和x2 如果变量增加，此代码有效：

> d1 <- data.frame(subject = c("id1", "id2"), x0 = c("male", "female"),
+ x1_2000 = 1:2,
+ x1_2005 = 5:6,
+ x2_2000 = 1:2,
+ x2_2005 = 5:6,
+ x3_2000 = 1:2,
+ x3_2005 = 5:6,
+ x4_2000 = 1:2,
+ x4_2005 = 5:6
+ ) 
> 
> d2 <- melt(d1, id=c("subject", "x0"))
> d2 <- transform(d2, time = str_replace(variable, "^.*_", ""),
+                     variable = str_replace(variable, "_.*$", ""))
> 
> d3 <- dcast(d2, subject+x0+time~variable)
> 
> d3
  subject     x0 time x1 x2 x3 x4
1     id1   male 2000  1  1  1  1
2     id1   male 2005  5  5  5  5
3     id2 female 2000  2  2  2  2
4     id2 female 2005  6  6  6  6

使用多个变量和一些时间不变的方式从宽到面重塑数据框

2 个答案: