R实战| 雷达图(Radar Chart)
雷达图(radar chart)，又称蜘蛛网图(spider plot)，是一种表现多维数据的强弱的图表。它将多个维度的数据量映射到坐标轴上，这些坐标轴起始于同一个圆心点，通常结束于圆周边缘，将同一组的点使用线连接起来就称为了雷达图。
本文以R包fmsb和 ggradar 为例介绍一下雷达图的绘制。
fmsb
install.packages("fmsb") library(fmsb)
# 示例数据 exam_scores <- data.frame( row.names = c("Student.1", "Student.2", "Student.3"), Biology = c(7.9, 3.9, 9.4), Physics = c(10, 20, 0), Maths = c(3.7, 11.5, 2.5), Sport = c(8.7, 20, 4), English = c(7.9, 7.2, 12.4), Geography = c(6.4, 10.5, 6.5), Art = c(2.4, 0.2, 9.8), Programming = c(0, 0, 20), Music = c(20, 20, 20) ) exam_scores
> exam_scores Biology Physics Maths Sport English Geography Art Programming Music Student.1 7.9 10 3.7 8.7 7.9 6.4 2.4 0 20 Student.2 3.9 20 11.5 20.0 7.2 10.5 0.2 0 20 Student.3 9.4 0 2.5 4.0 12.4 6.5 9.8 20 20
数据准备
数据要求：
第1行必须包含每个变量的最大值
第2行必须包含每个变量的最小值
列或变量的个数必须大于2
# 定义变量最大最小值 max_min <- data.frame( Biology = c(20, 0), Physics = c(20, 0), Maths = c(20, 0), Sport = c(20, 0), English = c(20, 0), Geography = c(20, 0), Art = c(20, 0), Programming = c(20, 0), Music = c(20, 0) ) rownames(max_min) <- c("Max", "Min") # 合并数据 df <- rbind(max_min, exam_scores) df
> df Biology Physics Maths Sport English Geography Art Programming Music Max 20.0 20 20.0 20.0 20.0 20.0 20.0 20 20 Min 0.0 0 0.0 0.0 0.0 0.0 0.0 0 0 Student.1 7.9 10 3.7 8.7 7.9 6.4 2.4 0 20 Student.2 3.9 20 11.5 20.0 7.2 10.5 0.2 0 20 Student.3 9.4 0 2.5 4.0 12.4 6.5 9.8 20 20
基础雷达图
#以student 1为例 library(fmsb) student1_data <- df[c("Max", "Min", "Student.1"), ] radarchart(student1_data)
进阶雷达图
参数设置
Variable options
vlabels: 变量标签
vlcex: 变量标签字体大小
Polygon options:
pcol: 线条颜色
pfcol: 填充颜色
plwd: 线条宽度
plty: 线条类型. 使用数字1-6或者字符向量 (“solid”, “dashed”, “dotted”, “dotdash”, “longdash”, “twodash”).使用 plty = 0 or plty = “blank”，不显示线条.
Grid options:
cglcol:网格线颜色
cglty: 网格线类型
cglwd: 网格线宽度
Axis options:
axislabcol: 轴标签和数字的颜色。默认设置是“蓝色”。
caxislabels: 字符向量，用作中心轴上的标签。
radarchart( student1_data, axistype = 1, # Customize the polygon pcol = "#00AFBB", pfcol = scales::alpha("#00AFBB", 0.5), plwd = 2, plty = 1, # Customize the grid cglcol = "grey", cglty = 1, cglwd = 0.8, # Customize the axis axislabcol = "grey", # Variable labels vlcex = 0.7, vlabels = colnames(student1_data), caxislabels = c(0, 5, 10, 15, 20))
多组雷达图
radarchart(
df, axistype = 1, # Customize the polygon pcol = c("#00AFBB", "#E7B800", "#FC4E07"), pfcol = scales::alpha(c("#00AFBB", "#E7B800", "#FC4E07"),0.5), plwd = 2, plty = 1, # Customize the grid cglcol = "grey", cglty = 1, cglwd = 0.8, # Customize the axis axislabcol = "grey", # Variable labels vlcex = 0.7, vlabels = colnames(student1_data), caxislabels = c(0, 5, 10, 15, 20)) # Add an horizontal legend legend( x = "bottom", legend = rownames(df[-c(1,2),]), horiz = TRUE, bty = "n", pch = 20 , col = c("#00AFBB", "#E7B800", "#FC4E07"), text.col = "black", cex = 1, pt.cex = 1.5 )
ggradar
devtools::install_github("ricardo-bion/ggradar") library("ggradar")
数据准备
library(tidyverse) # 将行名改为分组列 df <- exam_scores %>% rownames_to_column("group") df
> df group Biology Physics Maths Sport English Geography Art Programming Music 1 Student.1 7.9 10 3.7 8.7 7.9 6.4 2.4 0 20 2 Student.2 3.9 20 11.5 20.0 7.2 10.5 0.2 0 20 3 Student.3 9.4 0 2.5 4.0 12.4 6.5 9.8 20 20
基础雷达图
ggradar( df[1, ], values.radar = c("0", "10", "20"),# 最小，平均和最大网格线显示的值 grid.min = 0, # 绘制最小网格线的值 grid.mid = 10, # 绘制平均网格线的值 grid.max = 20 # 绘制最大网格线的值 )
进阶雷达图
ggradar( df[1, ], values.radar = c("0", "10", "20"), grid.min = 0, grid.mid = 10, grid.max = 20, # Polygons group.line.width = 1, group.point.size = 3, group.colours = "#00AFBB", # Background and grid lines background.circle.colour = "white", gridline.mid.colour = "grey" )
分组雷达图
ggradar( df, values.radar = c("0", "10", "20"), grid.min = 0, grid.mid = 10, grid.max = 20, # Polygons group.line.width = 1, group.point.size = 3, group.colours = c("#00AFBB", "#E7B800", "#FC4E07"), # Background and grid lines background.circle.colour = "white", gridline.mid.colour = "grey", legend.position = "bottom" )
Reference
https://www.datanovia.com/en/blog/beautiful-radar-chart-in-r-using-fmsb-and-ggplot-packages/
