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R实战| 雷达图(Radar Chart)

2022-02-05  本文已影响0人  木舟笔记
radarplot.jpg

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fmsbggradar 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:

# 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)
image-20220204210533508

进阶雷达图

参数设置

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))
image-20220204213805490

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
)
image-20220204214729670

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
)
image-20220204221014672

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"
)
image-20220204221102835

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"
  )
image-20220204221206017

Reference

往期

  1. 跟着Cell学作图 | Proteomaps图
  2. R实战 | 山脊图(ridgeline plot)
  3. GOplot | 更美观的富集分析可视化

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