ggpie饼图一站式解决方案，包含玫瑰图，甜甜圈图~-优快云博客

文章目录

pie plot
获取填充色
常规pie
donut
双变量甜甜圈图
- debug
单变量玫瑰图
双变量玫瑰图

pie plot

library(ggpie)
library(ggplot2)
library(tidyverse)

data(diamonds)
str(diamonds)

tibble [53,940 × 10] (S3: tbl_df/tbl/data.frame)
 $ carat  : num [1:53940] 0.23 0.21 0.23 0.29 0.31 0.24 0.24 0.26 0.22 0.23 ...
 $ cut    : Ord.factor w/ 5 levels "Fair"<"Good"<..: 5 4 2 4 2 3 3 3 1 3 ...
 $ color  : Ord.factor w/ 7 levels "D"<"E"<"F"<"G"<..: 2 2 2 6 7 7 6 5 2 5 ...
 $ clarity: Ord.factor w/ 8 levels "I1"<"SI2"<"SI1"<..: 2 3 5 4 2 6 7 3 4 5 ...
 $ depth  : num [1:53940] 61.5 59.8 56.9 62.4 63.3 62.8 62.3 61.9 65.1 59.4 ...
 $ table  : num [1:53940] 55 61 65 58 58 57 57 55 61 61 ...
 $ price  : int [1:53940] 326 326 327 334 335 336 336 337 337 338 ...
 $ x      : num [1:53940] 3.95 3.89 4.05 4.2 4.34 3.94 3.95 4.07 3.87 4 ...
 $ y      : num [1:53940] 3.98 3.84 4.07 4.23 4.35 3.96 3.98 4.11 3.78 4.05 ...
 $ z      : num [1:53940] 2.43 2.31 2.31 2.63 2.75 2.48 2.47 2.53 2.49 2.39 ...

获取填充色

library(ggsci)

cl=pal_lancet("lanonc", alpha = 0.9)(6)
cl

[1] "#00468BE5" "#ED0000E5" "#42B540E5" "#0099B4E5" "#925E9FE5" "#FDAF91E5"

常规pie

输入数据：dataframe类长数据；
参数意义：

group_key：关注的分类变量；
count_type:
对于原始数据（full）,对于已经拿到频数的数据可以直接使用count列的数据显示百分比（count）；
label_info：选择label的类型，仅显示个数（count），仅显示百分比（ratio），同时显示两者（all）;
label_type: label的朝向，水平，circle或者没有label（none）；
label_split：以什么分隔符分离label_info = all时的label,
分隔符要存在于label中；
label_pos：在饼图内，还是外显示label；
label_threshold：当频率低于阈值时，label显示在饼图外；
fill_color：指定填充色；

# with no label
ggpie(data = diamonds, 
      group_key = "cut", 
      count_type = "full",
      label_info = "all", 
      label_type = "horizon", 
      fill_color = cl[1:5],
      label_split = "[[:space:]]+",
      label_size = 4, 
      label_pos = "in", 
      label_threshold = 10)

agg_data <- table(diamonds$cut) %>% 
  as.data.frame() %>% 
  setNames(c("cut", "count"))

count_type = "count"输入数据已经计算了频数可以直接使用。

ggpie(data = agg_data, 
      group_key = "cut", 
      count_type = "count",      # 使用该列的值
      label_info = "all",
      label_type = "horizon", 
      label_split = "[[:space:]]+",
      label_size = 4, 
      label_pos = "in", 
      label_threshold = 10)

donut

甜甜圈图

ggdonut(data = diamonds, 
        group_key = "cut", 
        count_type = "full",
        label_info = "all", 
        label_type = "horizon",
        fill_color = cl[1:5],
        label_size = 4, 
        label_pos = "in", 
        label_threshold = 10)

双变量甜甜圈图

只能接受两个分类变量
问题：inner label ratio小数点位数过长

inner_label_threshold：小于阈值的label不显示；

p <- ggnestedpie(data = diamonds, 
            group_key = c("color", "cut"), 
            count_type = "full", 
            r0 = 0.5, r1 = 1.7, r2 = 2.8,
            inner_label_info = "ratio", 
            inner_label_split = NULL,
            inner_label_threshold = 2, 
            inner_label_size = 2,
            inner_fill_color = cl[1:5],
            outer_label_type = "horizon", 
            outer_label_pos = "in",
            outer_label_info = "ratio", 
            outer_label_threshold = 10,
            outer_fill_color = NULL)
print(p)

debug

解决inner pie显示比例小数点位数冗余的问题。
通过ggplot_build和ggplot_gtable直接对上述生成的ggplot对象自行修改。

# 格式化函数
format_percent <- function(x) {
  # 如果是空字符串，直接返回
  if (x == "" || is.na(x)) return(x)
  
  # 提取数字部分（去掉 %）
  num <- sub("%", "", x)
  
  # 转为数值，四舍五入到小数点后2位
  rounded <- round(as.numeric(num), 2)
  
  # 格式化为字符串并加 %，确保总是保留两位小数（如 5.00%）
  sprintf("%.2f%%", rounded)
}


p.build = ggplot_build(p)
p.build$data[[2]]$label = sapply(p.build$data[[2]]$label, format_percent, USE.NAMES = FALSE)
final.plot <- ggplot_gtable(p.build)

plot(final.plot)

单变量玫瑰图

tick_break：自定义频数刻度；

# pie plot
p1=ggrosepie(diamonds, group_key = "color", count_type = "full", label_info = "all",
             tick_break = c(3000,5000,7000,11000), donut_frac=NULL)
# donut plot
p2=ggrosepie(diamonds, group_key = "color", count_type = "full", label_info = "all",
             tick_break = c(3000,5000,7000,11000), donut_frac=0.3,donut_label_size=3)
cowplot::plot_grid(p1,p2)

双变量玫瑰图

可以发现上述直接使用cowplot::plot_grid(p1,p2)拼图得到的玫瑰图，图列冗余。在此处通过单独提取图例的方式，分别拼接没有图例的两个主图和图例即可优化整体布局。

library(ggpie)
library(cowplot)

# Step 1: 创建无图例的 pie plot
p1 <- ggrosepie(diamonds, 
                group_key = c("color", "cut"),
                count_type = "full", 
                label_info = "all",
                show_tick = FALSE,
                donut_frac = NULL) +
  theme(legend.position = "none")

# Step 2: 创建带图例的 donut plot（用于提取水平图例）
p2_with_legend <- ggrosepie(diamonds, 
                            group_key = c("color", "cut"),
                            count_type = "full", 
                            label_info = "all",
                            show_tick = FALSE,
                            donut_frac = 0.3,
                            donut_label_size = 3) +
  theme(
    legend.position = "bottom",        # 图例放在图下方
    legend.box = "horizontal",         # 图例项水平排列
    legend.text = element_text(size = 9),
    legend.title = element_text(size = 10, face = "bold")
  )

# Step 3: 提取图例
legend <- get_legend(p2_with_legend)

# Step 4: 创建无图例的 p2 用于拼图
p2 <- p2_with_legend + theme(legend.position = "none")

# Step 5: 拼接两个主图（p1 和 p2）
plot_main <- plot_grid(
  p1, p2,
  ncol = 2,
  align = "h",
  rel_heights = c(1, 1)
)

# Step 6: 将主图与水平图例拼接（图例在下方）
plot_final <- plot_grid(
  plot_main,  # 上部分：两个图形
  legend,     # 下部分：横向图例
  ncol = 1,
  rel_heights = c(1, 0.15),  # 主图占大部分高度，图例占小部分
  align = "v"
)

print(plot_final)