如何将含多选答案的R数据集转换为虚拟变量格式？

针对你的数据集（注意原代码中why_are_you_sad的元素数量与subjects不匹配，已先修正），可以用tidyverse工具包高效生成对应5个选项的虚拟变量，步骤如下：

1. 修正并准备数据集 #

首先调整数据集中的长度不匹配问题：

df <- data.frame(subjects = 1:12,
                 Why_are_you_not_happy = 
                   c(1,2,"1,2,5",5,1,2,"3,4",3,2,"1,5",3,4),
                 why_are_you_sad = 
                   c("1,2,3",1,2,3,"4,5,3",2,1,4,3,1,1) ) # 移除原代码中多余的最后一个"1"

2. 加载必要工具包 #

library(tidyverse)

3. 拆分多选项并生成虚拟变量 #

处理「不开心原因」列 #

将逗号分隔的选项拆分为多行，再转换为宽格式的虚拟变量（1代表选中该选项，0代表未选中）：

happy_dummies <- df %>%
  select(subjects, Why_are_you_not_happy) %>%
  separate_rows(Why_are_you_not_happy, sep = ",") %>%
  # 强制包含1-5所有选项，避免无人选的选项被遗漏
  mutate(Why_are_you_not_happy = factor(Why_are_you_not_happy, levels = 1:5)) %>%
  mutate(value = 1) %>%
  pivot_wider(names_from = Why_are_you_not_happy, 
              values_from = value, 
              names_prefix = "happy_",
              values_fill = 0)

处理「悲伤原因」列 #

用相同逻辑处理第二个问题列：

sad_dummies <- df %>%
  select(subjects, why_are_you_sad) %>%
  separate_rows(why_are_you_sad, sep = ",") %>%
  mutate(why_are_you_sad = factor(why_are_you_sad, levels = 1:5)) %>%
  mutate(value = 1) %>%
  pivot_wider(names_from = why_are_you_sad, 
              values_from = value, 
              names_prefix = "sad_",
              values_fill = 0)

4. 合并结果到最终数据集 #

将生成的虚拟变量与原受试者ID合并：

final_df <- df %>%
  select(subjects) %>%
  left_join(happy_dummies, by = "subjects") %>%
  left_join(sad_dummies, by = "subjects")

# 查看最终结果
print(final_df)

运行后会得到包含happy_1至happy_5、sad_1至sad_5的虚拟变量列，完整对应每个问题的5个选项。

内容的提问来源于stack exchange，提问作者An116