以下代码根据分层聚类创建一个等值区域地图(使用hclust()
和cutree()
):
library(plotly)
library(cluster)
hc <- hclust(dist(df), method = "complete")
df$member <- cutree(hc, 5)
cluster.means = (as.data.frame(aggregate(df[,-1], list(cluster= df$member), mean)))[,-4]
g = list(
scope = 'africa',
showframe = T,
showland = T,
landcolor = toRGB("white")
)
plot_ly(df, z = member, type = 'choropleth', locations = Country,
locationmode = 'country names', text = Country, hoverinfo = "text") %>%
layout(geo = g, title = "Energy markets in Africa")
现在我想改变两件事:
cluster.means
我附上了这样一个关于我的想法的示例性情节(它不必看起来完全相同 - 只是为了传达这个想法)。
任何帮助,建议,tipp非常感谢!
(Scaled)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")
答案 0 :(得分:5)
&#34;理想情况下,我希望根本没有比例&#34; :这是通过将参数showscale=F
添加到plot_ly()
来实现的。
&#34;国家/地区的永久显示&#34; :这是通过添加scattergeo
绘图图层(如this post中所述)和未成年人来完成的区别。由于您的数据框包含一列国家/地区名称,但不包含国家/地区代码,因此您需要添加参数locationmode = 'country names'
p <- plot_ly(df, z = member, type = 'choropleth',
locations = Country, locationmode = 'country names',
text = Country, hoverinfo = "text",
showscale=F, inherit =F) %>%
layout(geo = g, title = "Energy markets in Africa") %>%
add_trace(type="scattergeo",
locationmode = 'country names', locations = Country,
text = Country, mode="text",
textfont = list(color=rgb(1,0.5,0.3), size =12))
您需要尝试各种配色方案才能找到有效显示群集的颜色方案,同时使永久国家/地区名称标签可见。当地图缩小时,永久国家/地区名称标签将相互重叠的事实可能很少。通过额外的努力,您可以为每个标签指定一个lat-long位置,而不是依赖于它们的默认位置,这可以通过更好地分离标签来帮助改善地图的外观。不过,我认为,既然您要求使用永久性标签,那么您打算只在合适的缩放位置使用地图才能显示确定。
要添加您描述的文本框,您可以使用注释布局(每个群集一个注释)。我在这里展示如何添加一个带有紫色边框和一个第二个绿松石边框。您需要将其调整为最终使用的配色方案。
box1 <- list(
x = 0.3,
y = 0.5,
yanchor = "top",
borderpad = 2,
bordercolor = rgb(0.5,0.1,0.5), # set this same as color of cluster 1
borderwidth = 5,
text = paste("1. Cluster, ",
sum(df$member==1), # number of countries in cluster
" Countries<br>X1 = ", # use <br> for line breaks
format(round(cluster.means[1,]$X1, 2), nsmall = 2),
"<br>X2 = ",
format(round(cluster.means[1,]$X2, 2), nsmall = 2)),
align = "left",
showarrow = F)
box2 <- list(
x = 0.3,
y = 0.4,
yanchor = "top",
borderpad = 2,
bordercolor = rgb(0.1,0.5,0.5),
borderwidth = 5,
text = paste("2. Cluster, ",
sum(df$member==2),
" Countries<br>X1 = ",
format(round(cluster.means[2,]$X1, 2), nsmall = 2),
"<br>X2 = ",
format(round(cluster.means[2,]$X2, 2), nsmall = 2)),
align = "left",
showarrow = F)
p %>% layout(annotations = list(box1, box2))