求助：基于R语言为activity和task_persistence创建堆叠分组条形图

1. 数据预处理 #

原数据框中的数值和误差区间均为字符格式，需先转换为数值型并拆分误差区间上下限：

library(tidyverse)
library(patchwork)

# 加载原始数据
rG_activity <- c("0.368", "0.468", "0.427", "0.091")
rG_activity_error_intervals <- c("(0.468, 0.268)", "(0.568, 0.368)", "(0.527, 0.327)", "(1.091, -0.909)")
rG_task_persistence <- c("-0.462", "-0.345", "-0.291", "-1.062")
rG_task_persistence_error_intervals <- c("(-0.562, -0.362)", "(-0.445, -0.245)", "(-0.391, -0.191)", "(-2.091, -0.062)")
rE_activity <- c("-0.162", "-0.245", "-0.129", "-0.462")
rE_activity_error_intervals <- c("(-0.262, -0.062)", "(-0.345, -0.145)", "(-0.229, -0.029)", "(-0.562, -0.362)")
rE_task_persistence <- c("-0.362", "-0.245", "-0.191", "-0.162")
rE_task_persistence_error_intervals <- c("(-0.462, -0.262)", "(-0.345, -0.145)", "(-0.291, -0.091)", "(-0.262, -0.062)")
age <- c("30", "24", "18", "12")
df <- data.frame(age, rG_activity, rG_activity_error_intervals, rG_task_persistence, rG_task_persistence_error_intervals, rE_activity, rE_activity_error_intervals, rE_task_persistence, rE_task_persistence_error_intervals)

# 清洗数据：转换数值类型、拆分误差区间
df_clean <- df %>%
  mutate(across(starts_with("r"), as.numeric)) %>%
  # 拆分activity类误差区间
  separate(rG_activity_error_intervals, into = c("rG_activity_upper", "rG_activity_lower"), sep = ", ", remove = TRUE) %>%
  separate(rE_activity_error_intervals, into = c("rE_activity_upper", "rE_activity_lower"), sep = ", ", remove = TRUE) %>%
  # 拆分task_persistence类误差区间
  separate(rG_task_persistence_error_intervals, into = c("rG_task_upper", "rG_task_lower"), sep = ", ", remove = TRUE) %>%
  separate(rE_task_persistence_error_intervals, into = c("rE_task_upper", "rE_task_lower"), sep = ", ", remove = TRUE) %>%
  # 去掉括号并转换为数值
  mutate(across(ends_with(c("upper", "lower")), ~ str_remove_all(., "\\(|\\)") %>% as.numeric())) %>%
  # 设置年龄为有序因子，保证绘图顺序正确
  mutate(age = factor(age, levels = c("12", "18", "24", "30")))

2. 数据重塑（宽转长） #

将宽格式数据转换为ggplot2适配的长格式，区分指标类型与分组：

df_long <- df_clean %>%
  pivot_longer(
    cols = -age,
    names_to = c("group", "indicator", "error_type"),
    names_pattern = "(rG|rE)_(activity|task_persistence)(_upper|_lower)?",
    values_to = "value"
  ) %>%
  mutate(
    error_type = ifelse(is.na(error_type), "estimate", error_type),
    indicator = factor(indicator, levels = c("activity", "task_persistence"))
  ) %>%
  pivot_wider(
    names_from = error_type,
    values_from = value
  )

3. 绘制上下堆叠的分组条形图 #

用ggplot2分别绘制两个指标的带误差区间分组条形图，再通过patchwork拼接，将图例统一置于底部：

# 定义统一绘图主题
plot_theme <- theme_minimal() +
  theme(
    legend.position = "bottom",
    legend.title = element_text(size = 10),
    axis.title.x = element_text(size = 11),
    axis.title.y = element_text(size = 11),
    plot.title = element_text(size = 12, hjust = 0.5)
  )

# 绘制Activity指标图
plot_activity <- df_long %>%
  filter(indicator == "activity") %>%
  ggplot(aes(x = age, y = estimate, fill = group)) +
  geom_col(position = position_dodge(width = 0.8), width = 0.7) +
  geom_errorbar(aes(ymin = lower, ymax = upper), 
                position = position_dodge(width = 0.8), width = 0.2) +
  labs(title = "Activity指标", x = "年龄", y = "数值") +
  plot_theme

# 绘制Task Persistence指标图
plot_task <- df_long %>%
  filter(indicator == "task_persistence") %>%
  ggplot(aes(x = age, y = estimate, fill = group)) +
  geom_col(position = position_dodge(width = 0.8), width = 0.7) +
  geom_errorbar(aes(ymin = lower, ymax = upper), 
                position = position_dodge(width = 0.8), width = 0.2) +
  labs(title = "Task Persistence指标", x = "年龄", y = "数值") +
  plot_theme

# 拼接图形并合并图例
combined_plot <- plot_activity / plot_task +
  plot_layout(guides = "collect") &
  theme(legend.position = "bottom", legend.title = element_text(label = "分组"))

# 显示最终图形
print(combined_plot)

关键说明 #

• 数据预处理：确保数值类型正确，拆分误差区间并转换为数值，有序因子保证年龄顺序符合逻辑。
• 数据重塑：通过pivot系列函数将宽数据转为长数据，方便按指标和分组筛选绘图。
• 绘图细节：position_dodge实现分组条形效果，geom_errorbar添加误差区间；patchwork的/操作符实现上下堆叠，plot_layout(guides = "collect")合并图例并置于底部。

内容的提问来源于stack exchange，提问作者wooden05