意外转换为字符而不是数据帧和矩阵中的因素 [英] Unexpected conversion to chars instead of factors in data frames and matrices

问题描述

我不是R的新手用户，但以下是最令人困惑的。

我有一个数据框（虽然问题同样适用于矩阵）值为+ 1 / -1的分类变量，我想转换为因子。

  mat<  -  matrix （样本（c（-1，+1），16，replace = T），nrow = 4）
 mat<  -  data.frame（mat）
  pre> 
 
 
但是，使用
  mat<  -  apply ，2，factor）
  
将整数变成字符而不是因素：
 > mat 
 [，1] [，2] [，3] [，4] 
 [1，]-11-11
 [ ]-1-1-1-1
 [3，]-1111
 [4，]-1 -111
  
也许在同一静脉（和我有一个问题这样我的一些其他数据）尝试将矩阵和数据框中的字符名称转换为因素导致更混乱的行为：
  mat2<  - 矩阵（样本（字母，16，替换= T），nrow = 4）
> mat2 
 [，1] [，2] [，3] [，4] 
 [1，]xmre
 [2，] urbp
 [3，]jphj
 [4，]ksex 
 
 mat2 [，1]<  -  factor（mat2 [，1]）$ ​​b $ b> mat2 
 [，1] [，2] [，3] [，4] 
 [1，]4mre
 [2，] 3rbp
 [3，]1phj
 [4，]2sex 
  
任何帮助或澄清将不胜感激。
解决方案
永远记住，数据帧是列表，所以在列上操作就像迭代列表的元素。我想也许你打算做这样的事情：
  mat []<  -  lapply（mat，factor）
  
或此：
  as.data.frame（lapply（mat，factor））
  
虽然这里，请注意，每个因素的水平不一样！
 
I am not a novice user of R, but the following is most confusing.

I have a data frame (although the problem is equally present for matrices) of categorical variables taking the values +1/-1, which I'd like to convert into factors.
mat <- matrix(sample(c(-1, +1), 16, replace = T), nrow = 4)
mat <- data.frame(mat)
However, using 
mat <- apply(mat, 2, factor)
turns integers into characters instead of factors: 
> mat 
     [,1] [,2] [,3] [,4]
[1,] "-1" "1"  "-1" "1" 
[2,] "-1" "-1" "-1" "-1"
[3,] "-1" "1"  "1"  "1" 
[4,] "-1" "-1" "1"  "1" 
Perhaps in the same vein (and I had a problem of this sort with some of my other data) trying to convert character names in matrices and data frames into factors results in more confusing behaviour:
 mat2 <- matrix(sample(letters, 16, replace = T), nrow = 4)
 > mat2
     [,1] [,2] [,3] [,4]
 [1,] "x"  "m"  "r"  "e" 
 [2,] "u"  "r"  "b"  "p" 
 [3,] "j"  "p"  "h"  "j" 
 [4,] "k"  "s"  "e"  "x" 

mat2[,1] <- factor(mat2[,1])
> mat2
     [,1] [,2] [,3] [,4]
 [1,] "4"  "m"  "r"  "e" 
 [2,] "3"  "r"  "b"  "p" 
 [3,] "1"  "p"  "h"  "j" 
 [4,] "2"  "s"  "e"  "x" 
any help or clarification would be appreciated.
解决方案
Always remember that data frames are lists, and so operating on columns is just like iterating over elements of a list. I think maybe you intended to do something more like this:
mat[] <- lapply(mat,factor)
or this:
as.data.frame(lapply(mat,factor))
Although even here, note that the levels of each factor are not the same!

                        
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