R语言环形分组柱状图定制：替换标签为国家名称

核心改动说明 #

要把图表里的Individual标签换成真实国家名，核心是替换模拟数据为你的真实国家数据，并调整代码中引用标签的字段：

1. 导入真实数据 #

替换原来生成模拟数据的代码，读取你的国家数据（假设表格包含country（国家名）、group（分组：Am/As/E/Af）、value三个核心列）：

# 先安装并加载必要包
install.packages("dplyr")
install.packages("ggplot2")
install.packages("googlesheets4")

library(dplyr)
library(ggplot2)
library(googlesheets4)

# 读取你的表格数据
data <- read_sheet("1hxZROTPoSb8bmVrdpvZsYzbSjjkuCzBw")
# 调整分组名称为目标的Am、As、E、Af（根据表格实际分组名修改映射）
data <- data %>% mutate(group = recode(group, 
                                       "America" = "Am", 
                                       "Asia" = "As",
                                       "Europe" = "E",
                                       "Africa" = "Af")) %>%
  arrange(group, value)

2. 调整标签引用 #

原代码中所有引用individual的地方，替换为你的国家名列（假设列名为country），尤其是geom_text里的标签参数。

3. 修正代码小错误 #

原代码里ggplot的数据源写的是global，必须改为data，否则会报错。

修改后的完整代码 #

# 加载必要包
library(dplyr)
library(ggplot2)
library(googlesheets4)

# 读取真实国家数据
data <- read_sheet("1hxZROTPoSb8bmVrdpvZsYzbSjjkuCzBw")
# 匹配目标分组名称
data <- data %>% 
  mutate(group = recode(group, 
                        "America" = "Am", 
                        "Asia" = "As",
                        "Europe" = "E",
                        "Africa" = "Af")) %>%
  arrange(group, value)

# 设置每组末尾的空栏数
empty_bar <- 3
to_add <- data.frame(matrix(NA, empty_bar * nlevels(factor(data$group)), ncol(data)))
colnames(to_add) <- colnames(data)
to_add$group <- rep(levels(factor(data$group)), each = empty_bar)
data <- rbind(data, to_add)
data <- data %>% arrange(group)
data$id <- seq(1, nrow(data))

# 准备标签角度与位置
label_data <- data
number_of_bar <- nrow(label_data)
angle <- 90 - 360 * (label_data$id - 0.5) / number_of_bar
label_data$hjust <- ifelse(angle < -90, 1, 0)
label_data$angle <- ifelse(angle < -90, angle + 180, angle)

# 准备分组基线数据
base_data <- data %>% 
  group_by(group) %>% 
  summarize(start = min(id), end = max(id) - empty_bar) %>% 
  rowwise() %>% 
  mutate(title = mean(c(start, end)))

# 准备网格刻度数据
grid_data <- base_data
grid_data$end <- grid_data$end[c(nrow(grid_data), 1:nrow(grid_data)-1)] + 1
grid_data$start <- grid_data$start - 1
grid_data <- grid_data[-1,]

# 绘制环形柱状图
p <- ggplot(data, aes(x = as.factor(id), y = value, fill = group)) +
  geom_bar(stat = "identity", alpha = 0.5) +
  
  # 添加水平刻度线
  geom_segment(data = grid_data, aes(x = end, y = 80, xend = start, yend = 80), 
               colour = "grey", alpha = 1, size = 0.3, inherit.aes = FALSE) +
  geom_segment(data = grid_data, aes(x = end, y = 60, xend = start, yend = 60), 
               colour = "grey", alpha = 1, size = 0.3, inherit.aes = FALSE) +
  geom_segment(data = grid_data, aes(x = end, y = 40, xend = start, yend = 40), 
               colour = "grey", alpha = 1, size = 0.3, inherit.aes = FALSE) +
  geom_segment(data = grid_data, aes(x = end, y = 20, xend = start, yend = 20), 
               colour = "grey", alpha = 1, size = 0.3, inherit.aes = FALSE) +
  
  # 添加刻度数值标签
  annotate("text", x = rep(max(data$id), 4), y = c(20, 40, 60, 80), 
           label = c("20", "40", "60", "80"), color = "grey", size = 3, 
           angle = 0, fontface = "bold", hjust = 1) +
  
  ylim(-100, 120) +
  theme_minimal() +
  theme(
    legend.position = "none",
    axis.text = element_blank(),
    axis.title = element_blank(),
    panel.grid = element_blank(),
    plot.margin = unit(rep(-1, 4), "cm")
  ) +
  coord_polar() +
  # 替换为国家名称标签
  geom_text(data = label_data, aes(x = id, y = value + 10, label = country, hjust = hjust), 
            color = "black", fontface = "bold", alpha = 0.6, size = 2.5, 
            angle = label_data$angle, inherit.aes = FALSE) +
  
  # 添加分组基线与名称
  geom_segment(data = base_data, aes(x = start, y = -5, xend = end, yend = -5), 
               colour = "black", alpha = 0.8, size = 0.6, inherit.aes = FALSE) +
  geom_text(data = base_data, aes(x = title, y = -18, label = group), 
            hjust = c(1,1,0,0), colour = "black", alpha = 0.8, size = 4, 
            fontface = "bold", inherit.aes = FALSE)

# 显示图表
p

关键注意点 #

• 如果表格中国家名列不是country，请把代码里的country替换为实际列名
• 若读取表格遇到权限问题，可先将表格导出为CSV，用read.csv("你的文件路径.csv")读取
• 调整recode函数里的分组映射，确保和你的表格原始分组名称匹配

内容的提问来源于stack exchange，提问作者Ana-Maria