r：根据使用 cutree() 的层次聚类的等值线图

Question

我正在对 50 个不同的非洲国家/地区的两个参数 (X1, X2) 进行层次聚类。因此，我想在非洲大陆内识别出 5 个不同的 groups/clusters。我正在使用以下代码来执行此操作：

hc <- hclust(dist(df), method = "complete")
member <- cutree(hc, 5)

现在，我想使用 member 中存储的信息（即每个国家所属的集群 ID）为非洲地图着色，以便每个集群都用另一种颜色表示。我知道有很多关于着色地图的教程，比如this。但我想知道是否有针对层次聚类分析结果的特定地图着色方法？

有人做过吗？我很高兴就如何以最有效的方式实现这一目标提出任何建议或建议！

（缩放）数据如下所示：

df <- structure(list(Country = structure(1:50, .Label = c("Angola", 
"Benin", "Botswana", "Burkina Faso", "Burundi", "Cabo Verde", 
"Cameroon", "Central African Republic", "Chad", "Comoros", "Congo", 
"Cote d'Ivoire", "Democratic Republic of Congo", "Djibouti", 
"Equatorial Guinea", "Eritrea", "Ethiopia", "Gabon", "Gambia", 
"Ghana", "Guinea", "Guinea-Bissau", "Kenya", "Lesotho", "Liberia", 
"Madagascar", "Malawi", "Mali", "Mauritania", "Mauritius", "Mozambique", 
"Namibia", "Niger", "Nigeria", "Reunion", "Rwanda", "Sao Tome and Principe", 
"Senegal", "Seychelles", "Sierra Leone", "Somalia", "South Africa", 
"South Sudan", "Sudan", "Swaziland", "Tanzania", "Togo", "Uganda", 
"Zambia", "Zimbabwe"), class = "factor"), X1 = c(-0.18, -1.03, 
0.6, 1.55, 0.22, 0.26, 0.76, 2.15, -1.43, 0.99, 1.79, -0.39, 
1.73, 1.57, 1.11, -0.09, -1.49, -0.46, -0.48, -1.22, -0.78, -1.46, 
-1.22, 0.35, 0.45, 1.29, -1.37, -0.61, 0.92, -1.3, 0.42, -1.18, 
1.4, -0.83, 0.06, -0.76, -0.19, -0.37, -0.63, 0.64, 0.93, 0.33, 
-0.76, -0.21, -0.59, -0.41, -0.74, 0.39, -1.1, 1.35), X2 = c(-0.22, 
-0.42, 0.72, -0.59, -1.27, 0.64, -1.35, -1.4, -0.35, -1.43, 1.07, 
-0.01, -0.51, 0.11, 1.14, -0.89, 0.77, 1.45, -1.67, -0.83, 0.71, 
0.92, 1.63, 1.68, 0.23, -0.18, 0.07, 0.8, -0.02, 0.82, -0.72, 
-0.41, -0.26, 0.02, -1.68, 1.67, 0.18, 0.98, 1.45, 0.31, -1.23, 
-1.38, -0.63, 1.41, -0.12, 0, -1.3, -1.64, 0.21, 1.52)), .Names = c("Country", 
"X1", "X2"), row.names = c(NA, -50L), class = "data.frame")

Answer 1

使用您的数据并绘制：

library(plotly)


hc <- hclust(dist(df), method = "complete")
df$member <- cutree(hc, 5)


#Grabbing the Africa Geo from a plotly example
g <- list(
  scope = 'africa',
  showframe = F,
  showland = T,
  landcolor = toRGB("grey90")
)

plot_ly(df, z = member, type = 'choropleth', mode = 'markers', locations = Country,
    locationmode = 'country names') %>% layout(geo = g)

您可以使用此处的绘图设置：https://plot.ly/r/reference/

切换到非连续比例尺，但碰巧连续比例尺仅适用于绘制 5。要获得更多，您需要发散色标尺。

r：根据使用 cutree() 的层次聚类的等值线图

r: Choropleth map according to hierarchial clustering using cutree()

r

cluster-analysis

choropleth