R语言UpSet包实现集合可视化示例详解

R语言UpSet包实现集合可视化示例详解

UpSetR包是专门用于集合可视化的一个R包，当多集合的韦恩图不容易看的时候，UpSetR包就能派上用场。本文将详细介绍如何使用UpSetR包进行集合可视化，包括基本参数设置、queries参数的使用以及如何添加属性图等。

一、R包及数据

# 安装及加载R包
# install.packages("UpSetR")
library(UpSetR)

# 载入数据集
data <- read.csv("upSet.csv", header = TRUE)

# 先大致浏览一下该数据集, 数据集太长，就只看前几列
head(data[, 1:6], 6)
# View(data) # 弹出窗口，可查看数据

二、upset()函数

使用UpsetR包里面的upset()函数绘制集合可视化图形。

1）基本参数

upset(data,
      sets = c("Action", "Adventure", "Comedy", "Drama", "Fantasy", "Children", "Crime"), # 查看特定的几个集合
      mb.ratio = c(0.55, 0.45), # 控制上方条形图以及下方点图的比例
      order.by = "freq", # 如何排序，这里freq表示从大到小排序展示
      keep.order = TRUE, # keep.order按照sets参数的顺序排序
      number.angles = 30, # 调整柱形图上数字角度
      point.size = 2, line.size = 1, # 点和线的大小
      mainbar.y.label = "Genre Intersections", sets.x.label = "Movies Per Genre", # 坐标轴名称
      text.scale = c(1.3, 1.3, 1, 1, 1.5, 1)) # 六个数字，分别控制c(intersection size title, intersection size tick labels, set size title, set size tick labels, set names, numbers above bars)

2）queries参数

queries参数分为四个部分：query, param, color, active；

• query: 指定哪个query，UpSetR有内置，也可以自定义；
• param: list, query作用于哪个交集
• color：每个query都是一个list，里面可以设置颜色,没设置的话将调用包里默认的调色板；
• active：被指定的条形图：TRUE显示颜色，FALSE在条形图顶端显示三角形；

upset(data, main.bar.color = "black",
      queries = list(list(query = intersects, # UpSetR 内置的intersects query
                          params = list("Drama"), ## 指定作用的交集
                          color = "red", ## 设置颜色，未设置会调用默认调色板
                          active = F, # TRUE：条形图被颜色覆盖，FALSE：条形图顶端显示三角形
                          query.name = "Drama"), # 添加query图例
                     list(query = intersects, params = list("Action", "Drama"), active = T, query.name = "Emotional action"),
                     list(query = intersects, params = list("Drama", "Comedy", "Action"), color = "orange", active = T)),
      query.legend = "top")

3）attribute.plots参数

添加属性图，内置有柱形图、散点图、热图等

3.1 添加柱形图和散点图

upset(data, main.bar.color = "black",
      queries = list(list(query = intersects, params = list("Drama"), color = "red",
                          active = F, query.name = "Drama"),
                     list(query = intersects, params = list("Action", "Drama"), active = T, query.name = "Emotional action"),
                     list(query = intersects, params = list("Drama", "Comedy", "Action"), color = "orange", active = T)),
      attribute.plots = list(gridrows = 45, # 添加属性图
                             plots = list(
                               list(plot = scatter_plot, # 散点图
                                    x = "ReleaseDate", y = "AvgRating", # 横纵轴的变量
                                    queries = T), # T 则显示出上面queries定义的颜色
                               list(plot = histogram, x = "ReleaseDate", queries = F)),
                             ncols = 2), # 添加的图分两列
      query.legend = "top") # query图例在最上方

3.2 添加箱线图

每次最多添加两个箱线图

upset(movies, boxplot.summary = c("AvgRating", "ReleaseDate"))

3.3 添加密度曲线图

因默认属性图中没有密度曲线，需要自定义plot函数

# 自定义密度曲线
another.plot <- function(data, x, y) {
  data$decades <- round_any(as.integer(unlist(data[y])), 10, ceiling)
  data <- data[which(data$decades >= 1970), ]
  myplot <- (ggplot(data, aes_string(x = x)) + geom_density(aes(fill = factor(decades)),
                                                           alpha = 0.4) + theme(plot.margin = unit(c(0, 0, 0, 0), "cm"), legend.key.size = unit(0.4, "cm")))
}

upset(data, main.bar.color = "black", mb.ratio = c(0.5, 0.5), queries = list(list(query = intersects,
                                                                                  params = list("Drama"), color = "red", active = F), list(query = intersects,
                                                                                                                                         params = list("Action", "Drama"), active = T), list(query = intersects,
                                                                                                                                                                                        params = list("Drama", "Comedy", "Action"), color = "orange", active = T)),
      attribute.plots = list(gridrows = 50, plots = list(list(plot = histogram,
                                                              x = "ReleaseDate", queries = F), list(plot = scatter_plot, x = "ReleaseDate",
                                                                                                    y = "AvgRating", queries = T), list(plot = another.plot, x = "AvgRating",
                                                                                                                                         y = "ReleaseDate", queries = F)), ncols = 3))