根据数字的不同范围，将数字映射到R中的分类值 [英] Map numerics to categorical values in R, based on different ranges for the numerics

问题描述

希望我的头衔有意义。我有一个带有一列数字值的数据框，我想使用此列创建一个新列，从而根据其值将数字值映射到不同的存储桶中。下面是一些测试数据，以及我目前用于解决此问题的边缘粗糙的ifelse（）方法。我希望以一种不涉及嵌套ifelse（）语句的更好的方式对此进行编码，因为这种方法在许多存储桶中无法很好地扩展：

Hope my title makes sense. I have a dataframe with a column of numeric values, and I would like to use this column to create a new column whereby the numeric values are 'mapped' to different buckets based on their values. Below is some test data, as well as a rough-around-the-edges nested ifelse() approach that I am currently using to solve this problem. I am hoping to code this in a better way that doesn't involve nested ifelse() statements, since this approach doesn't scale well for many buckets:

mydf = data.frame(strings = letters[1:10], 
              numerics = c(0.2, 0.4, 1.3, 5.2, 3.3, 2.1, 7.3, 1.1, 4.3, 8.3),
              stringsAsFactors = FALSE)

这是我的测试数据框，这是我嵌套的ifelse （）解决我的问题的方法：

Here is my test dataframe, and here is my nested ifelse() approach to solving my problem:

mydf$buckets = ifelse(mydf$numerics <= 2, 0, 
                   ifelse(mydf$numerics <= 4, 1, 
                       ifelse(mydf$numerics <= 5, 2, 
                            ifelse(mydf$numerics <= 7, 3, 4))))

上面的代码所做的是将数值列中的值映射如下：

What the above code does is maps values in the numeric column as follows:

• 所有值<2变为0


• 所有值<4变为1


• 所有值< 5转到2


• 所有val ues< 7转到3


• 所有值> = 7转到4

• all values <2 go to 0
• all values <4 go to 1
• all values <5 go to 2
• all values <7 go to 3
• all values >= 7 to go 4

此这种方法不能很好地扩展少数几个存储桶。任何帮助，不胜感激！谢谢，

this approach doesn't scale well for more than a small number of buckets. any help with this is appreciated! Thanks,

推荐答案

我真的很喜欢在这种情况下使用 case_when 正如@tictocchoc在评论中已经提到的：

I really like using case_when in this sort of situation as already mentioned by @tictocchoc in the comments:

suppressPackageStartupMessages(library(tidyverse))

mydf = data.frame(strings = letters[1:10], 
                  numerics = c(0.2, 0.4, 1.3, 5.2, 3.3, 2.1, 7.3, 1.1, 4.3, 8.3),
                  stringsAsFactors = FALSE)

mydf %>%
  mutate(buckets = case_when(
    numerics < 2 ~0,
    numerics < 4 ~1,
    numerics < 5 ~2,    
    numerics < 7 ~3,
    numerics >= 7 ~4
  ))
#>    strings numerics buckets
#> 1        a      0.2       0
#> 2        b      0.4       0
#> 3        c      1.3       0
#> 4        d      5.2       3
#> 5        e      3.3       1
#> 6        f      2.1       1
#> 7        g      7.3       4
#> 8        h      1.1       0
#> 9        i      4.3       2
#> 10       j      8.3       4

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