由于您的数据点遍布世界各地，当您在一张地图上绘制所有内容时，可能很难区分地图上的点。作为替代方案，您可以创建一个多面图，其中包含世界多个地区的特写镜头。我建议以下步骤：
1：读取数据并确保它们具有正确的类：
coordinates <- read.csv2("seqmap.csv", header=T, fill=T,
col.names=c("ID.CODE", "latitude", "longitude", "sample.nature", "seq.methods"),
row.names=NULL)
coordinates$latitude <- as.numeric(as.character(coordinates$latitude))
coordinates$longitude <- as.numeric(as.character(coordinates$longitude))
2：加载所需的库：
library(ggplot2)
library(ggmap)
library(grid)
library(gridExtra)
3：创建点集群并将集群值分配给点：
km <- kmeans(coordinates[,c("longitude","latitude")], centers = 6)
coordinates$cluster <- km$cluster
4：获取不同集群的地图：
> km$centers
longitude latitude
1 -156.7000 71.37000
2 -88.3875 28.82875
3 -39.0700 -17.65200
4 139.3400 35.88667
5 94.4150 -67.29500
6 -64.5000 32.17000
map1 <- get_map(location = c(lon = -156.7, lat = 71.37), zoom = 7)
map2 <- get_map(location = c(lon = -88.3875, lat = 28.82875), zoom = 9)
map3 <- get_map(location = c(lon = -39.07, lat = -17.652), zoom = 9)
map4 <- get_map(location = c(lon = 139.34, lat = 35.88667), zoom = 8)
map5 <- get_map(location = c(lon = 94.415, lat = -67.295), zoom = 4)
map6 <- get_map(location = c(lon = -64.5, lat = 32.17), zoom = 10)
5：创建地图并将它们存储为对象：
p1 <- ggmap(map1) +
geom_point(data=coordinates[coordinates$cluster==1,], aes(x=longitude, y=latitude, shape=sample.nature, fill=seq.methods), size=3) +
scale_shape_manual(values=c("sediment"=21,"water"=22)) +
scale_fill_manual(values=c("Illumina"="red")) +
guides(shape=FALSE, fill=FALSE) +
ggtitle("Alaska")
p2 <- ggmap(map2) +
geom_point(data=coordinates[coordinates$cluster==2,], aes(x=longitude, y=latitude, shape=sample.nature, fill=seq.methods), size=3) +
scale_shape_manual(values=c("sediment"=21,"water"=22)) +
scale_fill_manual(values=c("Illumina"="red","ion torrent"="green")) +
guides(shape=FALSE, fill=FALSE) +
ggtitle("New Orleans")
p3 <- ggmap(map3) +
geom_point(data=coordinates[coordinates$cluster==3,], aes(x=longitude, y=latitude, shape=sample.nature, fill=seq.methods), size=3) +
scale_shape_manual(values=c("water"=22)) +
scale_fill_manual(values=c("454"="blue")) +
guides(shape=FALSE, fill=FALSE) +
ggtitle("Brazil")
p4 <- ggmap(map4) +
geom_point(data=coordinates[coordinates$cluster==4,], aes(x=longitude, y=latitude, shape=sample.nature, fill=seq.methods), size=3) +
scale_shape_manual(values=c("sediment"=21)) +
scale_fill_manual(values=c("454"="blue")) +
guides(shape=FALSE, fill=FALSE) +
ggtitle("Japan")
p5 <- ggmap(map5) +
geom_point(data=coordinates[coordinates$cluster==5,], aes(x=longitude, y=latitude, shape=sample.nature, fill=seq.methods), size=3) +
scale_shape_manual(values=c("water"=22)) +
scale_fill_manual(values=c("Sanger"="yellow")) +
guides(shape=FALSE, fill=FALSE) +
ggtitle("Antartica")
p6 <- ggmap(map6) +
geom_point(data=coordinates[coordinates$cluster==6,], aes(x=longitude, y=latitude, shape=sample.nature, fill=seq.methods), size=3) +
scale_shape_manual(values=c("water"=22)) +
scale_fill_manual(values=c("454"="blue","Illumina"="red")) +
guides(shape=FALSE, fill=FALSE) +
ggtitle("Bermuda")
6：创建单独的图例：
p0 <- ggplot(data=coordinates, aes(x=longitude, y=latitude, shape=sample.nature, fill=seq.methods, color=seq.methods)) +
geom_point(size=4) +
scale_shape_manual("Sample:",values=c("sediment"=21,"water"=22)) +
scale_fill_manual("Method:",values=c("454"="blue","Illumina"="red","ion torrent"="green","Sanger"="yellow")) +
scale_color_manual("Method:",values=c("454"="blue","Illumina"="red","ion torrent"="green","Sanger"="yellow")) +
theme(legend.key=element_rect(fill=NA))
# function to extract the legend (borrowed from: https://github.com/hadley/ggplot2/wiki/Share-a-legend-between-two-ggplot2-graphs )
g_legend<-function(a.gplot){
tmp <- ggplot_gtable(ggplot_build(a.gplot))
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
return(legend)}
legend <- g_legend(p0)
lwidth <- sum(legend$width)
7：创建最终情节：
grid.arrange(arrangeGrob(p1, p2, p3, p4, p5, p6, ncol=2),
legend, widths=unit.c(unit(1, "npc") - lwidth, lwidth), nrow=1)
给出以下结果：