“ 饼图（扇形图）时常用于对统计数据的可视化，在 R中，很多R包用于绘制饼图，例如ggplot2、ggsunburst就能绘制出好看的饼图，操作如下”

1. 加载所需要的包

library(RColorBrewer)  #调色模板
library(ggplot2)  #绘图
library(dplyr)  #数据处理、数据操作

2. 加载数据

#数据有3列，第一列是ID(Category)，第二列是数量(Count)，第三列是百分比(Percentage)
data <- data.frame(
  Category = c("NAC", "C2H2", "CAMTA", "mTERF", "ARID", "STAT", "CSD", "BES1", "GRAS", "NF-Y", "SNF2", "PHD", "MADS", "SRS", "HSF", "MBF1", "B3", "GNAT", "C3H", "FAR1", "GARP", "EIL", "DBB", "SET", "bHLH", "C2C2", "SOH1", "Tify", "TRAF", "MYB", "TCP", "HB", "DDT", "WRKY", "Jumonji", "SBP", "bZIP", "GeBP", "LIM", "TUB", "LOB", "OFP"),
  Count = c(21, 11, 1, 23, 5, 3, 2, 1, 19, 1, 7, 6, 41, 1, 12, 1, 13, 17, 14, 2, 3, 1, 8, 5, 13, 9, 2, 6, 5, 25, 2, 16, 1, 8, 2, 1, 2, 4, 4, 1, 2, 1),
  Percentage = c(6.52, 3.42, 0.31, 7.14, 1.55, 0.93, 0.62, 0.31, 5.90, 0.31, 2.17, 1.86, 12.73, 0.31, 3.73, 0.31, 4.04, 5.28, 4.35, 0.62, 0.93, 0.31, 2.48, 1.55, 4.04, 2.80, 0.62, 1.86, 1.55, 7.76, 0.62, 4.97, 0.31, 2.48, 0.62, 0.31, 0.62, 1.24, 1.24, 0.31, 0.62, 0.31)
)
#给Percentage列数值加上%
data$Percentage <- paste0(data$Percentage, "%")
得到如下数据：

数据中的Percentage列中百分比数值只是为了在饼图中作为label显示。具体扇形大小是根据Count列计算得到。

3. 数据处理 

#按照Category 的字母顺序排序（不区分大小写）
data <- data %>% arrange(tolower(Category))
#提取第1列和第3列
lbls<-(paste(data[,1],data[,3]))
#通过第二列数值计算每个ID的百分比
values <- data.frame(Percentage = round(data[,2]/sum(data[,2]) * 100,2), Type = factor(data[,1]),percent=lbls )
#创建因子
values$percent <- factor(values$percent, levels = values$percent)
#获得lab.yops列，该列为图中label的显示位置
values <- values %>%
  arrange(desc(Type)) %>% # 重排序
  mutate(lab.ypos = cumsum(Percentage) - 0.5*Percentage) 

4. 绘图

#利用ggplot2绘图
pie = ggplot(values, aes(x = "" ,y = Percentage, fill = percent)) + geom_bar(width = 3, stat = "identity")
print(pie)

#分别给色块添加label,其中百分比<3%的不显示balel,colo颜色，size字体大小
pie = pie + geom_text(aes(y=lab.ypos,label=ifelse(Percentage>3,as.character(percent),"")),color="black",size=5)
#将条形图转化为饼图，start=0默认从12点方向开始，theme_void()将灰色坐标轴、网格线等默认背景去除，
pie = pie + coord_polar("y",start = 0)+theme_void()
#添加标题
pie = pie + labs(fill="",title="pieplot")+theme(plot.title = element_text(hjust=0.5,size = 20))
#根据RColorBrewer包中颜色模板进行颜色设置，根据自己条目的多少选择颜色数量
colours= c(brewer.pal(9,"Set1"),brewer.pal(8,"Set2"),brewer.pal(12,"Set3"),brewer.pal(12,"Paired"),brewer.pal(8,"Accent"),brewer.pal(8,"Pastel2"))
pie = pie + scale_fill_manual(values =colours)
print(pie)

之后可以利用修图软件对图片进行调整，将饼中label角度进行旋转，会更美观一些。在刚才数据基础上进行环形饼图绘制

#width = 2.3用于控制条形的宽度，这里影响扇区的宽度。color="white",size=0.5，给每个条形设置白色边框，并调整宽度
pie = ggplot(values, aes(x = "",y = Percentage, fill = percent)) + geom_bar(width = 2.3, stat ="identity",color="white",size=1.5)
#将条形图转化为饼图
pie = pie + coord_polar("y",start = 0)+theme_void()
#加了一个位于饼图中心的文本标签allcoun是数值总和
allcount=sum(data$Count)
pie = pie + geom_text(aes(y=lab.ypos,label=""),color="black",size=5)+
    geom_text(aes(x = -0.5, y = sum(Percentage)/2, label = allcount),size = 6, fontface = "bold", color = "black")
#添加标题，并将图例位置进行调整
pie = pie +labs(fill="",title="pieplot")+
    theme(plot.title = element_text(hjust = 0.5,size = 20),legend.text = element_text(size=18),
          legend.position = "bottom",legend.box = "vertical")
#修改颜色
colours = c(brewer.pal(9,"Set1"),brewer.pal(8,"Set2"),brewer.pal(12,"Set3"),brewer.pal(12,"Paired"),brewer.pal(8,"Accent"),brewer.pal(8,"Pastel2"))
pie = pie + scale_fill_manual(values =colours)
print(pie)

之后利用ggsunburst R包绘制多层环形饼图。在前一个数据基础上对Category列进行分类Group。

1. 加载所需要的包

library(ggplot2)
library(rpython2)
library(ggsunburst) #绘制多层环形饼图（旭日图）
library(RColorBrewer)

2. 加载数据

#数据有3列，第一列是分组(parent)，第二列是ID(node)，第三列是百分比(size)
data <- data.frame(
  parent = c("Group3", "Group3", "Group2", "Group2", "Group3", "Group5", "Group4", "Group1", "Group2", "Group3", "Group5", "Group3", "Group3", "Group1", "Group4", "Group1", "Group1", "Group5", "Group3", "Group2", "Group2", "Group1", "Group3", "Group4", "Group1", "Group3", "Group5", "Group4", "Group2", "Group5", "Group1", "Group1", "Group2", "Group3", "Group4", "Group5", "Group5", "Group3", "Group1", "Group2", "Group5", "Group5"),
  node = c("NAC", "C2H2", "CAMTA", "mTERF", "ARID", "STAT", "CSD", "BES1", "GRAS", "NF-Y", "SNF2", "PHD", "MADS", "SRS", "HSF", "MBF1", "B3", "GNAT", "C3H", "FAR1", "GARP", "EIL", "DBB", "SET", "bHLH", "C2C2", "SOH1", "Tify", "TRAF", "MYB", "TCP", "HB", "DDT", "WRKY", "Jumonji", "SBP", "bZIP", "GeBP", "LIM", "TUB", "LOB", "OFP"),
  size = c(6.52, 3.42, 0.31, 7.14, 1.55, 0.93, 0.62, 0.31, 5.90, 0.31, 2.17, 1.86, 12.73, 0.31, 3.73, 0.31, 4.04, 5.28, 4.35, 0.62, 0.93, 0.31, 2.48, 1.55, 4.04, 2.80, 0.62, 1.86, 1.55, 7.76, 0.62, 4.97, 0.31, 2.48, 0.62, 0.31, 0.62, 1.24, 1.24, 0.31, 0.62, 0.31)
)

3. 数据处理

#增加一列browser
data$browser<-data$parent 
#将数据以,分割的csv文件格式保存到本地
write.table(data, file = 'data.csv', row.names = F, sep = ",") 

4. 绘图

#利用sunburst_data函数读取csv文件内容
sb <- sunburst_data('data.csv', type = 'node_parent', sep = ",", node_attributes = c("browser","size"))
# 将名称添加为浏览器属性，用于为内部节点着色
sb$rects[!sb$rects$leaf,]$browser <- sb$rects[!sb$rects$leaf,]$name
#设置颜色
color_palette <- brewer.pal(5, "Set2")
names(color_palette) <- unique(sb$rects$browser[!is.na(sb$rects$browser)])
sb$rects$color <- color_palette[sb$rects$browser]
#利用sunburst函数绘图
p <- sunburst(sb, rects.fill=sb$rects$color, node_labels = T, node_labels.min = 15)
p + geom_text(data = sb$leaf_labels,aes(x=x, y=0.1, label=paste(size,"%"), angle=angle, hjust=hjust), size = 2)

之后可以利用修图软件对图片进行调整好了，小编就先给大家介绍到这里。希望对您的科研能有所帮助！祝您工作生活顺心快乐！

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