根据互斥的虚拟变量创建分类变量

Question

如何从互斥的虚拟变量（取值0/1）中创建分类变量？

基本上，我正在寻找与此解决方案（https://subscription.packtpub.com/book/big_data_and_business_intelligence/9781787124479/1/01lvl1sec22/creating-dummies-for-categorical-variables）完全相反的地方。

将不胜感激的是基本的R解决方案（没有dplyr，tibble，tidyverse等）。>>

例如，从这里开始：

dummy.df<-structure(c(1L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 
0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 
0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 1L), .Dim = c(10L, 4L
), .Dimnames = list(NULL, c("State.NJ", "State.NY", "State.TX", 
"State.VA")))

> dummy.df
      State.NJ State.NY State.TX State.VA
 [1,]        1        0        0        0
 [2,]        0        1        0        0
 [3,]        1        0        0        0
 [4,]        0        0        0        1
 [5,]        0        1        0        0
 [6,]        0        0        1        0
 [7,]        1        0        0        0
 [8,]        0        0        0        1
 [9,]        0        0        1        0
[10,]        0        0        0        1
我想转到此处

cat.var<-structure(list(state = structure(c(1L, 2L, 1L, 4L, 2L, 3L, 1L, 
4L, 3L, 4L), .Label = c("NJ", "NY", "TX", "VA"), class = "factor")), class = "data.frame", row.names = c(NA, 
-10L))

> cat.var
   state
1     NJ
2     NY
3     NJ
4     VA
5     NY
6     TX
7     NJ
8     VA
9     TX
10    VA

如何从互斥的虚拟变量（取值0/1）中创建分类变量？基本上，我正在寻找与此解决方案完全相反（https：//subscription.packtpub ....

Answer 1

# toy data
df <- data.frame(a = c(1,0,0,0,0), b = c(0,1,0,1,0), c = c(0,0,1,0,1))

df$cat <- apply(df, 1, function(i) names(df)[which(i == 1)])

Answer 2

您可以做：

Answer 3

编辑：带有您的数据

Answer 4

您可以使用tidyr::gather：