R语言使用ggplot按Road分图绘制period分组的clusterNum统计柱状图

• 第一步：先对原始数据做聚合统计，按Road、period、clusterNum三个维度分组，计算每个分组的观测数量
• 第二步：分组柱状图绘制逻辑：x轴映射为period，y轴映射为统计得到的数量，填充色映射为clusterNum，柱状图位置设置为并排排列
• 第三步：按Road拆分图的两种实现方式：
  • 方式1：使用facet_wrap按Road分面，在同一张画布生成多个子图，适合做整体对比
  • 方式2：循环过滤不同Road的子集分别绘图，可单独导出每张图到本地

1. 加载依赖包 #

library(dplyr)
library(ggplot2)

2. 构造示例数据 #

data <- structure(list(clusterNum = c(2, 2, 2, 2, 2, 3, 2, 3, 3, 3),Road = c("Hualampong", "Hualampong", "Hualampong", "Hualampong","Hualampong", "Hualampong", "Hualampong", "Tonglor", "Tonglor","Tonglor"), period = c("06.00-06.15", "06.00-06.15", "06.16-06.30","06.16-06.30", "06.16-06.30", "06.16-06.30", "06.16-06.30","17.46-18.00", "17.46-18.00", "17.46-18.00")), row.names = c(NA,-10L), class = c("tbl_df", "tbl", "data.frame")) 

3. 数据聚合统计 #

count_df <- data %>%
  group_by(Road, period, clusterNum) %>%
  summarise(cnt = n(), .groups = "drop")

4. 绘图实现 #

方式1：分面生成同画布多张子图 #

ggplot(count_df, aes(x = period, y = cnt, fill = as.factor(clusterNum))) +
  geom_col(position = position_dodge(width = 0.9), width = 0.8) +
  facet_wrap(~Road, scales = "free") +
  labs(x = "时间段", y = "统计数量", fill = "clusterNum") +
  theme_bw() +
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

方式2：单独生成每张Road的独立图片 #

# 提取所有道路名称
road_unique <- unique(count_df$Road)

# 循环生成并导出图片
for (road_name in road_unique) {
  sub_df <- filter(count_df, Road == road_name)
  p <- ggplot(sub_df, aes(x = period, y = cnt, fill = as.factor(clusterNum))) +
    geom_col(position = position_dodge(width = 0.9), width = 0.8) +
    labs(title = road_name, x = "时间段", y = "统计数量", fill = "clusterNum") +
    theme_bw() +
    theme(axis.text.x = element_text(angle = 45, hjust = 1))
  # 导出到本地，文件名为对应道路名称
  ggsave(paste0(road_name, "_分组柱状图.png"), p, width = 6, height = 4, dpi = 300)
}

内容的提问来源于stack exchange，提问作者Yasumin