R实现地图相关图形绘制

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地图相关图形绘制具有许多优点，这些优点使其在各种领域和应用中非常有用。例如：地图相关图形提供了一种直观的方式来可视化数据，使数据更容易理解和分析。通过地图，可以看到数据的空间分布，识别趋势和模式，并从中获取有关地理位置的见解。下面使用R语言绘制地图相关图。

（1）数据

使用美国50个州2005年的收入分配不均等指数，其中的6个收入不均等指数，除了泰尔熵指数之外，均介于0到1之间，数值越大代表收入分配越不均匀。详细数据在文末。

（2）收入不均等指数数据整理与点状图绘制

library(lattice)
ineq50=read.csv("ineq50.csv", header=F)
names(ineq50)=c("ATKIN05","GINI","RMEANDEV","THEIL","TOP1","TOP10")
save(ineq50, file="ineq50.RData")
load("ineq50.RData")
attach(ineq50)
vn=colnames(ineq50)
j=2
index=ineq50[,vn[j]]
data=data.frame(name = state.name,region = state.region,y=index)
name=state.name
region=state.region
dotplot(reorder(name, index)~index, ineq50, main=c("Inequality Index"),xlab=vn[j])

输出结果：

通过图像可以发现，康涅狄格州的收入分配最不平均，西弗吉尼亚州则最好。

（3）实现切段绘图

b=0.9 # Define cutting point
cuts =shingle(index,intervals = rbind(c(0, b),c(b, 2)))
dotplot(reorder(name, index) ~ index| cuts , ineq50,
strip = FALSE, layout = c(2, 1), levels.fos = 1:50,
scales = list(x = "free"), between = list(x = 0.5),
xlab = "Theil income inequality index",
par.settings = list(layout.widths = list(panel = c(2, 1))))

输出结果：

（4）按地理区域呈现收入不均等指数数据

ineq50$region=with(ineq50, reorder(region, index, median))
ineq50$name=with(ineq50,reorder(reorder(name, index), as.numeric(region)))

dotplot(name~ index | region, ineq50, strip = F, strip.left = T, layout = c(1, 4),
scales = list(y = list(relation = "free")),xlab = vn[j])

输出结果：

（5）在美国地图上呈现收入不均等指数

state.info = data.frame(name = state.name,long = state.center$x,lat = state.center$y,y=index)
library(maps)
state.map = map("state", plot=FALSE, fill = FALSE)
panel.3dmap = function(..., rot.mat, distance, xlim, ylim, zlim,
xlim.scaled, ylim.scaled, zlim.scaled)
{
scaled.val = function(x, original, scaled) {
scaled[1] + (x - original[1]) * diff(scaled) / diff(original)
}
m = ltransform3dto3d(rbind(scaled.val(state.map$x, xlim, xlim.scaled),
scaled.val(state.map$y, ylim, ylim.scaled),zlim.scaled[1]),
rot.mat, distance)
panel.lines(m[1,], m[2,], col = "grey76")
}

cloud(index ~ long + lat, state.info,
subset = !(name %in% c("Alaska", "Hawaii")),
panel.3d.cloud = function(...) {
panel.3dmap(...)
panel.3dscatter(...)
},
type = "h", scales = list(draw = FALSE), zoom = 1.2,xlim = state.map$range[1:2],
ylim = state.map$range[3:4],xlab = NULL, ylab = NULL, zlab = NULL,
aspect = c(diff(state.map$range[3:4])/diff(state.map$range[1:2]), 0.3),
panel.aspect = 0.75, lwd = 2, screen = list(z = 30, x = -70),
par.settings = list(axis.line = list(col = "transparent"),
box.3d = list(col = "transparent", alpha = 0)))

输出结果：