如何将变量变为定量？

Question

我有一个数据矩阵（900列和5000行），我想要做一个pca ..

该矩阵看起来非常好在Excel中（意味着所有的值都是定量的），但在我读我的文件在R中，并尝试运行pca代码，我得到一个错误，说“下面的变量不是定量的”，我得到一个非定量变量列表。

所以一般来说，一些变量是定量的，有些不是。 请参阅以下示例。 当我检查变量1时，它是正确和定量的..（随机的一些变量在文件中是定量的） 当我检查变量2时，它是不正确的和非定量的..（随机一些像这样的变量是非 - 定量在文件中）

> data$variable1[1:5] 
[1] -0.7617504 -0.9740939 -0.5089303 -0.1032487 -0.1245882 

> data$variable2[1:5] 
[1] -0.183546332959017 -0.179283451229594 -0.191165669598284 -0.187060515423038 
[5] -0.184409474669824 
731 Levels: -0.001841783473108 -0.001855956210119 ... -1,97E+05 

所以我的问题是，我怎么能将所有的非定量变量转化为定量？

缩短文件并没有帮助，因为这些值本身就是定量的。我不知道发生了什么事。 所以这里是我的原始文件链接< - https://docs.google.com/file/d/0BzP-YLnUNCdwakc4dnhYdEpudjQ/edit

我也试过下面给出的答案，但它仍然没有帮助。

那么让我告诉正是我做了什么，

> data <- read.delim("file.txt", header=T) 
> res.pca = PCA(data, quali.sup=1, graph=T) 
Error in PCA(data, quali.sup = 1, graph = T) : 
The following variables are not quantitative: batch 
The following variables are not quantitative: target79 
The following variables are not quantitative: target148 
The following variables are not quantitative: target151 
The following variables are not quantitative: target217 
The following variables are not quantitative: target266 
The following variables are not quantitative: target515 
The following variables are not quantitative: target530 
The following variables are not quantitative: target587 
The following variables are not quantitative: target620 
The following variables are not quantitative: target730 
The following variables are not quantitative: target739 
The following variables are not quantitative: target801 
The following variables are not quantitative: target803 
The following variables are not quantitative: target809 
The following variables are not quantitative: target819 
The following variables are not quantitative: target868 
The following variables a 
In addition: There were 50 or more warnings (use warnings() to see the first 50) 

Answer 1

考虑R的变量因素，如阿伦提及。因此它会生成一个data.frame（实际上是一个列表）。有许多方法可以解决这个问题，可以通过以下方式将其转换为数据矩阵;

matrix <- as.numeric(as.matrix(data)) 
dim(matrix) <- dim(data) 

现在，您可以在矩阵上运行PCA。

编辑：

扩展的例子了一下，查理的建议的第二部分将无法工作。复制下面的会话，看看它是如何工作的;

d <- data.frame(
a = factor(runif(2000)), 
b = factor(runif(2000)), 
c = factor(runif(2000))) 

as.numeric(d) #does not work on a list (data frame is a list) 

as.numeric(d$a) # does work, because d$a is a vecor, but this is not what you are 
# after. R converts the factor levels to numeric instead of the actual value. 

(m <- as.numeric(as.matrix(d))) # this does the rigth thing 
dim(m)      # but m loses the dimensions and is now a vector 

dim(m) <- dim(d)    # assign the dimensions of d to m 

svd(m)      # you can do the PCA function of your liking on m 

Answer 2

默认情况下，R将字符串强制为因子。这可能会导致意外的行为。关闭此默认选项有：

 read.csv(x, stringsAsFactors=F) 

可以，或者，强制因素与数字

 newVar<-as.numeric(oldVar)