在R中，如何通过不同的标签设置和保留自定义级别? [英] in R, how to set and retain custom levels in factor with different labels?

问题描述

在R中，如何设置和保留具有不同标签的自定义水平?

in R, how to set and retain custom levels in factor with different labels ?

也就是说，我想在一个因子的级别中设置自定义数字，这些数字值-要保留的整数而不是转换为"1、2、3等".

That is, I want to set custom numbers in the levels of a factor, and these numerical values - integers to be retained and not converted to "1, 2, 3 etc.".

我知道一种解决方案是将这些权重设置为标签"，但是随后我将丢失该因子的标签".

I know that one solution is to set these weights as Labels, but then I will missing the "labels" of the factor.

不保留因素之间的加权"距离.在R中，是否可以使用单个变量来实现类似的目标?

The "weighted" distance between factors is not retained. Is it possible in R, to achieve something like this, using a single variable ?

例如:

age_f <- factor( c(1, 10, 100), levels = c( 1, 10, 100 ), labels = c( "baby", "child", "old" ), ordered = T )

levels(age_f)
   [1] "baby"  "child" "old"  
labels(age_f)
   [1] "1" "2" "3"
 labels(levels(age_f))
    [1] "1" "2" "3"
 as.numeric(age_f)
    [1] 1 2 3

Desired output: 
 as.numeric(age_f)
        [1] 1 10 100

如果在R因子中不存在此参数，是否容易通过自定义函数产生这样的结果?

If this does not exists in R factors, it is easy to produce such result by a custom function?

推荐答案

您可以为此使用 labelled 包.

library(labelled)
labelled(c(1, 10, 100), c(baby = 1, child = 10 , old = 100))

<Labelled double>
[1]   1  10 100

Labels:
 value label
     1  baby
    10 child
   100   old

如果以后要将其转换为常规因子，则可以使用 to_factor .

If you later want to convert it into a regular factor you can use to_factor.

这篇关于在R中，如何通过不同的标签设置和保留自定义级别?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！