如何在R中按类别数量灵活过滤商品篮数据集？

我有如下数据框：

structure(list(CATEGORY = c("Edible, Vape", "Concentrate, Flower", 
"Concentrate, Flower", "Concentrate, Flower", "Edible", "Concentrate, Flower", 
"Edible, Vape", "Edible", "Concentrate, Flower", "Concentrate, Flower", 
"Edible", "Edible", "Edible", "Concentrate, Flower", "Edible", 
"Edible", "Edible", "Edible, Vape", "Edible", "Edible", "Concentrate, Flower", 
"Edible", "Concentrate, Flower", "Concentrate, Flower", "Concentrate, Flower", 
"Edible", "Concentrate, Flower", "Concentrate, Edible, Flower", 
"Concentrate, Flower", "Edible", "Concentrate, Edible, Flower", 
"Edible", "Concentrate, Edible, Flower", "Concentrate, Edible, Flower, Vape", 
"Concentrate, Edible, Flower", "Concentrate, Flower", "Edible", 
"Edible", "Edible", "Concentrate, Edible, Flower, Vape", "Concentrate, Flower", 
"Concentrate, Flower", "Edible", "Concentrate, Flower", "Concentrate, Flower", 
"Concentrate, Flower", "Concentrate, Flower", "Concentrate, Flower", 
"Concentrate, Flower", "Edible, Vape", "Concentrate, Flower", 
"Edible, Vape", "Concentrate, Edible, Flower", "Edible, Vape", 
"Concentrate, Flower", "Edible", "Concentrate, Flower", "Concentrate, Flower", 
"Edible", "Concentrate, Flower", "Edible, Vape", "Edible", "Concentrate, Edible, Flower, Vape", 
"Edible", "Edible", "Concentrate, Flower", "Concentrate, Flower", 
"Edible, Vape", "Concentrate, Flower", "Edible", "Edible", "Edible, Vape", 
"Edible", "Edible", "Edible", "Concentrate, Flower", "Edible", 
"Edible", "Concentrate, Flower", "Edible, Vape", "Concentrate, Flower", 
"Edible", "Edible", "Edible", "Edible", "Concentrate, Flower", 
"Edible, Vape", "Edible", "Concentrate, Flower", "Edible, Vape", 
"Concentrate, Flower", "Concentrate, Flower", "Concentrate, Flower", 
"Concentrate, Flower", "Edible", "Edible", "Edible", "Edible, Vape", 
"Concentrate, Flower", "Edible")), row.names = c(NA, -100L), class = c("tbl_df", 
"tbl", "data.frame"))

CATEGORY列的值为逗号分隔的类别组合，存在1个、2个、3个甚至更多类别的情况。执行unique(interesting_baskets_df$CATEGORY)后得到的唯一类别值如下：

[1] "Edible, Vape"                      "Concentrate, Flower"               "Edible"                            "Concentrate, Edible, Flower"      
[5] "Concentrate, Edible, Flower, Vape"

我希望仅保留包含1个或2个类别的记录（如"Edible"、"Edible, Vape"、"Concentrate, Flower"），但不想用dplyr::filter硬编码指定类别值，需要一个灵活方案，能根据需求选择保留含N个类别的记录，适配关联规则学习的不同分析场景。

解决方案 #

核心思路 #

通过统计CATEGORY值中逗号的数量判断类别数：

• 1个类别：逗号数量为0
• 2个类别：逗号数量为1
• N个类别：逗号数量为N-1

只需筛选出逗号数量 ≤ 目标类别数-1的记录即可。

方法1：Tidyverse 实现 #

结合dplyr和stringr实现灵活筛选，示例为保留1-2个类别的记录：

library(dplyr)
library(stringr)

# 定义要保留的最大类别数
max_categories <- 2

filtered_df <- interesting_baskets_df %>%
  filter(str_count(CATEGORY, ",") <= max_categories - 1)

若需保留3个及以下类别的记录，仅需修改max_categories的值为3。

方法2：基础R 实现 #

无需加载额外包，用gregexpr统计逗号数量：

max_categories <- 2

# 统计每个CATEGORY的逗号数量
comma_counts <- sapply(gregexpr(",", interesting_baskets_df$CATEGORY), function(x) sum(x != -1))

# 筛选记录
filtered_df <- interesting_baskets_df[comma_counts <= max_categories - 1, ]

通用函数封装 #

将逻辑封装为函数，方便重复调用：

filter_by_category_count <- function(df, col_name, max_count) {
  # 统计逗号数量
  comma_counts <- sapply(gregexpr(",", df[[col_name]]), function(x) sum(x != -1))
  # 返回筛选后的数据集
  return(df[comma_counts <= max_count - 1, ])
}

# 示例：保留1-2个类别的记录
filtered_df <- filter_by_category_count(interesting_baskets_df, "CATEGORY", 2)

# 示例：保留1-3个类别的记录
filtered_df_3 <- filter_by_category_count(interesting_baskets_df, "CATEGORY", 3)

内容的提问来源于stack exchange，提问作者hachiko