R语言绘制环状柱状堆积图+分组+显著性

无叠加、显著性的代码：

#设置工作环境
rm(list=ls())
setwd("D:/Desktop/0000/code-main/条形图")#加载R包
library(ggplot2) # Create Elegant Data Visualisations Using the Grammar of Graphics
library(tidyverse) # Easily Install and Load the 'Tidyverse'#加载数据（随机编写，无实际意义）
df <- read.table("无叠加.csv", header = T, sep = ",")
head(df)
df$group <- factor(df$group,levels = c("M","N","G","F")) # 这几个字母表示不同的组，对应数据表格的第一个大组：group
head(df)# ----------------------------------------
##计算标签角度
df2 <- as.data.frame(df[c(1:10,11:22,23:34,35:46,47:48),])  # 重点：分别为不同组的对应的行。注意对应数据理解
rownames(df2) <- 1:48
df2$group <- factor(df2$group,levels = c("M","N","G","F"))
df2$ID <- as.numeric(rownames(df2))
number_of_bar <- nrow(df2)
angle <-  90 - 360 * (df2$ID-0.5) /number_of_bar
df2$hjust<-ifelse(angle < -90, 1, 0)
df2$angle<-ifelse(angle < -90, angle+180, angle)
#创建标签数据及位置
df3 <- df2 %>% group_by(group) %>% summarize(start=min(ID), end=max(ID) - 4) %>% rowwise() %>% mutate(title=mean(c(start, end)))
df3$group <- factor(df3$group,levels = c("M","N","G","F"))# ----------------------------------------
#绘图
ggplot()+#手动添加辅助线geom_hline(yintercept = 0,lty="solid", color = "black",linewidth=0.6)+geom_hline(yintercept = 20,lty="solid", color = "grey80")+geom_hline(yintercept = 60,lty="solid", color = "grey80")+geom_hline(yintercept = 40,lty="solid", color = "grey80")+geom_hline(yintercept = 80,lty="solid", color = "grey80")+geom_hline(yintercept = 100,lty="solid", color = "grey80")+#柱状堆积图绘制geom_col(df, mapping=aes(group3, value, fill = group), color = "grey20", linewidth = 0.25, width = 0.8)+# y轴范围确定scale_y_continuous(limits = c(-25,150))+# 颜色scale_fill_manual(values = c("#4fbb98","#f46024","#dd6ab0","#7c8ebe"))+# 主题theme_void()+theme(legend.position = 'none')+# 手动添加显著性geom_text(data=df2, aes(x=ID, y=103, label=c("Contral", "ADOM", "LHy1","LHA", "LFA","SHy1","SHA","SFA","RHy1","RHA","  "," ","Contral", "ADOM", "LHy1","LHA", "LFA","SHy1","SHA","SFA","RHy1","RHA","  ","  ","Contral", "ADOM", "LHy1","LHA", "LFA","SHy1","SHA","SFA","RHy1","RHA","  ","  ","Contral", "ADOM", "LHy1","LHA", "LFA","SHy1","SHA","SFA","RHy1","RHA","  ","  "),hjust=hjust,color=group),fontface="bold", size=3,angle= df2$angle, inherit.aes = F)+#手动添加坐标geom_text(data=df2, x=-0.3,y=5,label="0",color="black",size=3)+geom_text(data=df2, x=-0.3,y=25,label="20",color="black",size=3)+geom_text(data=df2, x=-0.3,y=45,label="40",color="black",size=3)+geom_text(data=df2, x=-0.3,y=65,label="60",color="black",size=3)+geom_text(data=df2, x=-0.3,y=85,label="80",color="black",size=3)+geom_text(data=df2, x=-0.3,y=105,label="100",color="black",size=3)+#极坐标转换coord_polar(direction=1)+##分组标签geom_text(data=df3, aes(x = title, y = 140, label=group,color=group), hjust=c(1,1,0,0), angle=c(335,250,135,60), size=5, fontface="bold", inherit.aes = F)+#颜色scale_color_manual(values = c("#4fbb98","#f46024","#dd6ab0","#7c8ebe"))

带叠加、显著性的代码：

#设置工作环境
rm(list=ls())
setwd("D:/Desktop/0000/code-main/条形图")#加载R包
library(ggplot2) # Create Elegant Data Visualisations Using the Grammar of Graphics
library(tidyverse) # Easily Install and Load the 'Tidyverse'#加载数据（随机编写，无实际意义）
df <- read.table("叠加.csv", header = T, sep = ",")
head(df)
df$group <- factor(df$group,levels = c("M","N","G","F")) # 这几个字母表示不同的组，对应数据表格的第一个大组：group
head(df)# ----------------------------------------
##计算标签角度
df2 <- as.data.frame(df[c(1:10,51:62,103:114,155:166,207:208),]) 
rownames(df2) <- 1:48
df2$group <- factor(df2$group,levels = c("M","N","G","F"))
df2$ID <- as.numeric(rownames(df2))
number_of_bar <- nrow(df2)
angle <-  90 - 360 * (df2$ID-0.5) /number_of_bar
df2$hjust<-ifelse(angle < -90, 1, 0)
df2$angle<-ifelse(angle < -90, angle+180, angle)
#确定显著性标签位置
result <- aggregate(value ~ group3, data = df, sum)
#创建标签数据及位置
df3 <- df2 %>% group_by(group) %>% summarize(start=min(ID), end=max(ID) - 4) %>% rowwise() %>% mutate(title=mean(c(start, end)))
df3$group <- factor(df3$group,levels = c("M","N","G","F"))# ----------------------------------------
#绘图
ggplot()+#手动添加辅助线geom_hline(yintercept = 0,lty="solid", color = "black",linewidth=0.6)+geom_hline(yintercept = 20,lty="solid", color = "grey80")+geom_hline(yintercept = 60,lty="solid", color = "grey80")+geom_hline(yintercept = 40,lty="solid", color = "grey80")+geom_hline(yintercept = 80,lty="solid", color = "grey80")+geom_hline(yintercept = 100,lty="solid", color = "grey80")+#柱状堆积图绘制geom_col(df, mapping=aes(group3, value, fill = group), color = "grey20", linewidth = 0.5, width = 0.8)+#y轴范围确定scale_y_continuous(limits = c(-25,150))+#颜色scale_fill_manual(values = c("#4fbb98","#f46024","#dd6ab0","#7c8ebe"))+#主题theme_void()+theme(legend.position = 'none')+#手动添加显著性geom_text(data=df2, aes(x=ID, y=103, label=c("Contral", "ADOM", "LHy1","LHA", "LFA","SHy1","SHA","SFA","RHy1","RHA","  "," ","Contral", "ADOM", "LHy1","LHA", "LFA","SHy1","SHA","SFA","RHy1","RHA","  ","  ","Contral", "ADOM", "LHy1","LHA", "LFA","SHy1","SHA","SFA","RHy1","RHA","  ","  ","Contral", "ADOM", "LHy1","LHA", "LFA","SHy1","SHA","SFA","RHy1","RHA","  ","  "),hjust=hjust,color=group), fontface="bold", size=3, angle= df2$angle, inherit.aes = F)+#手动添加标签geom_text(data=df2, aes(x=ID, y=result$value+4, label=c("", "", "***","", "","","**","","","","","","", "", "**","", "","","","***","","","","","", "***", "***","***", "**","***","**","***","**","***","","","", "***", "","", "","","","**","**","","",""),color=group), fontface="bold", size=4, angle= df2$angle+90, inherit.aes = F)+ #标签#手动添加坐标及标题geom_text(data=df2,x=11,y=30, label="Biodegradation rate(%)",color="black",size=3.5)+geom_text(data=df2, x=-0.2,y=5,label="0",color="black",size=3)+geom_text(data=df2, x=-0.2,y=25,label="20",color="black",size=3)+geom_text(data=df2, x=-0.2,y=45,label="40",color="black",size=3)+geom_text(data=df2, x=-0.2,y=65,label="60",color="black",size=3)+geom_text(data=df2, x=-0.2,y=85,label="80",color="black",size=3)+geom_text(data=df2, x=-0.2,y=105,label="100",color="black",size=3)+#极坐标转换coord_polar(direction=1)+##分组标签geom_text(data=df3, aes(x = title, y = 140, label=group,color=group), hjust=c(1,1,0,0), angle=c(335,250,135,60), size=5, fontface="bold", inherit.aes = F)+#颜色scale_color_manual(values = c("#4fbb98","#f46024","#dd6ab0","#7c8ebe"))