在建模之前减少因子水平的数量 [英] Reducing number of factor levels before modelling

问题描述

我有一个2600级的因子，我想在建模之前将其降低到〜10

I have a factor with 2600 levels and I want to reduce it to ~10 before modelling

我想我可以通过一个操作来做到这一点，如果列出的因子少于x次，应将其放入称为其他的存储桶中。

I thought I could do this with an operation that says "if a factor is listed fewer than x times, it should be placed into a bucket called "other"

以下是一些示例数据：

df <- data.frame(colour=c("blue","blue","blue","green","green","orange","grey"))

这是我希望得到的输出：

And this is the output I am hoping for:

  colour
1   blue
2   blue
3   blue
4  green
5  green
6  other
7  other

我尝试了以下操作：

df %>% mutate(colour = ifelse(count(colour) < 2, 'other', colour))

mutate_impl（.data，点）中的错误：
评估错误：否

Error in mutate_impl(.data, dots) : Evaluation error: no applicable method for 'groups' applied to an object of class "factor".

推荐答案

tidyverse中实际上有一个名为 forcats 的不错的程序包，它可以帮助处理因素。您可以使用 fct_lump ，它确实满足您的需求：

There is actually a nice package in the tidyverse called forcats which helps in dealing with factors. You can use fct_lump, which does exactly what you need:

library(tidyverse)

df %>% mutate(colour = fct_lump(colour, n = 2))
#>   colour
#> 1   blue
#> 2   blue
#> 3   blue
#> 4  green
#> 5  green
#> 6  Other
#> 7  Other

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