ggplot2分组条形图中因子顺序失效问题求助

尝试用ggplot2绘制分组条形图，希望每个日期分组内的条形按count值排序，但ggplot2似乎忽略了因子水平，无法实现预期效果。可复现代码如下：

library(ggplot2)
library(dplyr)
library(forcats)

set.seed(42)
daily_data <- expand.grid(
  date = seq.Date(from = as.Date("2024-01-01"), to = as.Date("2024-01-10"), by = "1 day"),
  location = c("West", "East", "North")
) %>%
  mutate(count = sample(10:100, size = n(), replace = TRUE))

daily_data <- daily_data %>%
  group_by(date) %>%
  mutate(location = fct_reorder2(location, date, count)) %>%
  ungroup()

p <- ggplot(daily_data, aes(x = factor(date), y = count, fill = location)) +
  geom_col(stat = "identity", position = "dodge") +
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

print(p)

已尝试方法：

• 使用factor()手动设置因子水平
• 在mutate调用及aes()的fill参数中使用fct_reorder()和fct_reorder2()

核心问题在于：ggplot2中分组条形的顺序由全局因子水平决定，group_by()后用fct_reorder()只能在组内临时排序，无法保留每组独立的顺序。要实现每个日期组内按count排序，需创建包含date和location的交互变量，按count排序后作为x轴变量，再调整x轴标签显示日期即可。

修改后的完整代码：

library(ggplot2)
library(dplyr)
library(forcats)

set.seed(42)
daily_data <- expand.grid(
  date = seq.Date(from = as.Date("2024-01-01"), to = as.Date("2024-01-10"), by = "1 day"),
  location = c("West", "East", "North")
) %>%
  mutate(count = sample(10:100, size = n(), replace = TRUE))

# 创建date和location的交互变量，按count降序排序（.desc=TRUE改为FALSE可实现升序）
daily_data <- daily_data %>%
  group_by(date) %>%
  mutate(date_loc = fct_reorder(interaction(date, location), count, .desc = TRUE)) %>%
  ungroup()

p <- ggplot(daily_data, aes(x = date_loc, y = count, fill = location)) +
  geom_col(stat = "identity") +
  # 将x轴标签还原为原始日期，去掉交互变量中的location后缀
  scale_x_discrete(labels = function(x) gsub("\\..*", "", x)) +
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

print(p)

1. interaction(date, location)将日期和地点合并为唯一组合变量，对应每个独立条形
2. fct_reorder(..., count, .desc = TRUE)让每个日期组内的条形按count值降序排列
3. scale_x_discrete(labels = ...)把x轴标签还原为原始日期，避免显示交互变量的冗余后缀

内容的提问来源于stack exchange，提问作者Sam Swanson