本文介绍了使用ggplot从SpatialPolygonsDataFrame创建一个choropleth的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧! 问题描述 我有一个来自UScensus2010包的SpatialPolygonsDataFrame。我试图创造一个choropleth。当我这样做时,它会按预期工作: data(colorado.county10) choropleth(colorado.county10, P0010001, color = list(fun =rainbow, attr = list(4)), main =2010美国县, type =plot, border =black) 但由于'p0010001'未被发现 data(colorado.county10) ggplot(colorado.county10,aes(long, lat = group = group))+ geom_polygon(aes(fill = P0010001),color = alpha(white,1/2),size = 0.2)+ scale_fill_brewer(pal =PuRd ) 正如我试图弄清楚这一点,我注意到colorado.county10 $ P0010001返回一个数组数组,但是colorado.county10 [,P0010001]返回一个SpatialPolygonsDataFrame。 对发生了什么的深入了解解决方案如果y你需要使用 ggplot ,你需要从 SpatialPolygonsDataFrame 强制转换为 data.frame 。 ggplot2 提供了一些 fortify 方法来创建正确格式化的数据。 目前, fortify.SpatialPolygonsDataFrame 方法不会保留 data 组件,它提供了一个列 id ,其中包含数据中的rownames。在原始 SpatialPolygonsDataFrame 的 data 插槽内的 。注意, data.frames 是一种低效的方式来存储这些信息(每个多边形的每个顶点有1行)。 因此,以下内容可以正常工作,但速度很慢,可能会导致内存问题。 c10 c10d ggplot(c10d,aes(long,lat,group = group))+ geom_polygon(aes(fill = factor(P0010001)),color = alpha(white,1/2),size = 0.2) + scale_fill_brewer(pal =PuRd) 使用 base 绘图功能将更快,并且不会咀嚼尽可能多的资源。 I have a SpatialPolygonsDataFrame that comes from the UScensus2010 package. I am trying to create a choropleth. When I do so, this works as expected:data(colorado.county10)choropleth(colorado.county10, "P0010001", color = list(fun = "rainbow", attr = list(4)), main="2010 US Counties", type="plot", border="black")but this fails due to 'P0010001' not being founddata(colorado.county10)ggplot(colorado.county10, aes(long, lat, group = group)) + geom_polygon(aes(fill = P0010001), colour = alpha("white", 1/2), size = 0.2) + scale_fill_brewer(pal = "PuRd")As I've tried to figure this out, I've noted that colorado.county10$P0010001 returns an array of numbers, but colorado.county10[,"P0010001"] returns a SpatialPolygonsDataFrame.Any insights into what is happening? 解决方案 If you want to use ggplot you need to coerce from a SpatialPolygonsDataFrame to a data.frame.ggplot2 provides a number of fortify methods that will create the correctly formatted data.Currently the fortify.SpatialPolygonsDataFrame method does not retain the data component, it does provide a column id which contains the rownames from the data.frame within the data slot of the original SpatialPolygonsDataFrame. Note that data.frames are an inefficient way to store this information (1 row for each vertex for each polygon).Thus the following will work, but is slow and may cause memory issuesc10 <- fortify(colorado.county10)c10d <- cbind(c10, colorado.county10@data[c10$id,])ggplot(c10d, aes(long, lat, group = group)) + geom_polygon(aes(fill = factor(P0010001)), colour = alpha("white", 1/2), size = 0.2) + scale_fill_brewer(pal = "PuRd") Using base plotting functions will be much faster and not chew up as many resources. 这篇关于使用ggplot从SpatialPolygonsDataFrame创建一个choropleth的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持! 09-27 00:16