SCI图片复现：扇形图

2023-6-22

# 加载所需的包
library(ggplot2)
library(dplyr)

# 构建数据框
disease_proportion <- c(24.2, 21.9, 7.6, 5.2, 4.3, 3.2, 2.6, 2.6, 1.8, 1.8, 24.8)
disease_type <- c("Heart disease", "Cancer","Injuries", "CPD", "Stroke",'Type2 diabetes', "AD","Suicide","IP","Chronic liver disease","Other")
group_type <- rep("male", length(disease_proportion)) 
data <- data.frame(group_type, disease_type, disease_proportion) 

# 构建扇形图数据
data <- data %>% 
  mutate(proportion = disease_proportion/sum(disease_proportion)) %>% # 计算各个疾病的比例
  arrange(desc(disease_type)) %>% # 按疾病名称的降序排序
  mutate(position = cumsum(proportion)-0.5*proportion) # 计算每个扇形的中心位置
data$x_end <- ifelse(data$proportion < 0.2, 2, 1.8) # 计算标签指示线的结束位置

# 生成扇形图
plot <- ggplot(data, aes(x = "", y = proportion, fill = disease_type)) + # 使用各个疾病的比例为填充变量
  geom_bar(width = 1, stat = "identity", color = "white") + # 绘制堆叠条形图
  coord_polar("y", start = 0, clip = "off") + # 将条形图转换为极坐标（扇形图）
  geom_segment(aes(x = 1.5, y = position, xend = x_end, yend = position), size =0.5, color = 'black') + # 添加指示线
  geom_text(aes(y = position, x = x_end, label = paste(disease_type, scales::percent(proportion))), size = 4, color = "black") + # 添加标签
  scale_fill_manual(values = c("#aeae5c", "#FB8072", "#1965B0", "#7BAFDE","#882E72","#B17BA6", "#FF7F00", "#FDB462","#E7298A", "#E78AC3","#33A02C")) + # 定义填充色
  labs(x = NULL, y = NULL) + # 移除x和y标签
  theme_void() + # 移除所有的非数据组件
  theme(legend.position = "none") # 移除图例

# 显示图表
print(plot)

# 保存图表为 PDF
ggsave(plot, filename = "pie_chart.pdf", width = 10, height = 10)

# 保存数据为 CSV
write.csv(data, "data.csv", row.names = FALSE)

如果要使用自己的数据，那么数据应该有一个类似的格式，即一个数据框，至少包含以下三列：

群体（Group）：分类变量，用于表示个体属于哪一组。
疾病（disease）：分类变量，表示个体的疾病类别。
值（value）：数值变量，表示各类疾病的值（可能是频数，比例或其他度量）。

结果图片：

阅读剩余

THE END