R语言使用ggplot将10个非互斥变量绘制成单张分面条形图

你需要先将宽格式的数据集转换为长格式，再统计每个年龄组下各选项的选择占比，最后用ggplot绘图即可，完整实现代码如下：

# 加载所需依赖包
library(tidyverse)

# 导入示例数据集
df <- structure(list(improvement___1 = c(1, 0, 1, 1, 1, 1, 1, 1, 0, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), improvement___2 = c(0, 
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 
0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 
0, 0, 1), improvement___3 = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 
1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0), improvement___4 = c(1, 
0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 
1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 
1, 1, 1), improvement___5 = c(0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 
0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0), improvement___6 = c(0, 
1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 
0, 1, 1), improvement___7 = c(0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 
0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 
1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0), improvement___8 = c(0, 
1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 
0, 1, 1), improvement___9 = c(1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 
1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 
1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1), improvement___10 = c(0, 
0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0), AgeGroups = structure(c(2L, 1L, 2L, 1L, 2L, 1L, 3L, 
1L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 3L, 1L, 2L, 2L, 1L, 
2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 3L, 2L, 2L, 3L, 2L, 2L, 3L, 
3L, 1L, 2L, 3L, 1L, 2L, 1L), .Label = c("Young", "Middle", "Old"
), class = "factor")), row.names = c(NA, -46L), class = c("tbl_df", 
"tbl", "data.frame"))

# 数据预处理：宽表转长表，统计各年龄组各选项的选择比例
plot_data <- df %>%
  # 把所有improvement开头的列整合为长格式
  pivot_longer(cols = starts_with("improvement___"),
               names_to = "option",
               values_to = "selected") %>%
  # 提取选项编号用于排序
  mutate(option_num = as.integer(str_extract(option, "\\d+$"))) %>%
  # 按年龄组、选项分组计算选择率
  group_by(AgeGroups, option_num) %>%
  summarise(select_rate = mean(selected), .groups = "drop")

# 绘制分面条形图
ggplot(plot_data, aes(x = factor(option_num), y = select_rate)) +
  geom_col(fill = "#2c7fb8") +
  # 按年龄组分面，可调整nrow参数修改排布方式
  facet_wrap(~AgeGroups, nrow = 1) +
  labs(x = "选项编号", y = "选择比例") +
  # 把y轴转换为百分比格式
  scale_y_continuous(labels = scales::percent_format(accuracy = 1)) +
  # 优化显示主题
  theme_bw() +
  theme(
    panel.grid.major.x = element_blank(),
    strip.background = element_rect(fill = "#f0f0f0")
  )

关键说明 #

• 宽表转长表是核心操作，将分散在10列的选项数据整合为结构化的长格式，才能统一映射到ggplot的坐标轴
• 直接对0/1的选中状态求均值即可得到对应组的选择比例，无需额外计数
• 如果需要将x轴的选项编号替换为实际的问题选项文本，只需在mutate步骤新增对应关系的option_label列，再把x轴映射改为option_label即可

内容的提问来源于stack exchange，提问作者Joe Crozier