在ggplot的地图上绘制饼图

问题描述

这可能是一个愿望清单，不确定(即可能需要创建 geom_pie 才能发生这种情况).我今天看到了一张地图()中对我的回应关于居中县名将有助于这个概念.

我们如何使用 ggplot2 制作上面的地图?

一个数据集和没有饼图的地图:

load(url("http://dl.dropbox.com/u/61803503/nycounty.RData"))头(纽约)；head(key) #从我的下拉框中查看数据集图书馆(ggplot2)ggplot(ny, aes(long, lat, group=group)) + geom_polygon(colour='black', fill=NA)# 现在我们如何绘制每个县的种族饼图#(饼图的大小也可以通过大小来控制# 参数与其他 `geom_` 函数一样).

提前感谢您的想法.

我刚刚在

我使用了以下资源来实现这一点(链接将提供更详细的信息):

1. ggtree 博客
2. 移动ggplot图例
3. 正确的 ggtree 版本
4. 以多边形为中心

代码如下:

load(url("http://dl.dropbox.com/u/61803503/nycounty.RData"))头(纽约)；head(key) #从我的下拉框中查看数据集if (!require("pacman")) install.packages("pacman")p_load(ggplot2, ggtree, dplyr, tidyr, sp, maps, pipeR, grid, XML, gtable)getLabelPoint <- function(county) {Polygon(county[c('long', 'lat')])@labpt}df <- map_data('county', 'new york') # 纽约地区县数据centroids <- by(df, df$subregion, getLabelPoint) # 返回列表centroids <- do.call("rbind.data.frame", centroids) # 转换为数据帧names(centroids) <- c('long', 'lat') # 适当的标题pops <-http://data.newsday.com/long-island/data/census/county-population-estimates-2012/"%>%readHTMLTable(which=1) %>%tbl_df() %>%选择(1:2)%>%setNames(c("region", "population")) %>%变异(人口= {as.numeric(gsub(\ D"，"，人口))}，region = tolower(gsub("\s+[Cc]ounty|\.", "", region)),#weight = ((1 - (1/(1 + exp(population/sum(population)))))/11)权重 = exp(人口/总和(人口))，重量 = sqrt(重量/总和(重量))/3)Race_data_long <- add_rownames(centroids, "region") %>>%left_join({distinct(select(ny, region:other))}) %>>%left_join(pops) %>>%(~race_data)%>>%收集(种族，道具，白色:其他)%>%split(., .$region)馅饼<- setNames(lapply(1:length(race_data_long), function(i){ggplot(race_data_long[[i]], aes(x=1, prop, fill=race)) +geom_bar(stat="identity", width=1) +coord_polar(theta="y") +主题树() +xlab(NULL) +ylab(NULL) +主题透明() +主题(plot.margin=unit(c(0,0,0,0)，mm"))})，名称(race_data_long))e1 

This may be a wish list thing, not sure (i.e. maybe there would need to be the creation of geom_pie for this to occur). I saw a map today (LINK) with pie graphs on it as seen here.

I don't want to debate the merits of a pie graph, this was more of an exercise of can I do this in ggplot?

I have provided a data set below (loaded from my drop box) that has the mapping data to make a New York State map and some purely fabricated data on racial percentages by county. I have given this racial make up as a merge with the main data set and as a separate data set called key. I also think Bryan Goodrich's response to me in another post (HERE) on centering county names will be helpful to this concept.

How can we make the map above with ggplot2?

A data set and the map without the pie graphs:

load(url("http://dl.dropbox.com/u/61803503/nycounty.RData"))
head(ny); head(key)  #view the data set from my drop box
library(ggplot2)
ggplot(ny, aes(long, lat, group=group)) +  geom_polygon(colour='black', fill=NA)

#  Now how can we plot a pie chart of race on each county
#  (sizing of the pie would also be controllable via a size
#  parameter like other `geom_` functions).

Thanks in advance for your ideas.

EDIT: I just saw another case at junkcharts that screams for this type of capability:

解决方案

Three years later this is solved. I've put together a number of processes together and thanks to @Guangchuang Yu's excellent ggtree package this can be done fairly easily. Note that as of (9/3/2015) you need to have version 1.0.18 of ggtree installed but these will eventually trickle down to their respective repositories.

I've used the following resources to make this (the links will give greater detail):

1. ggtree blog
2. move ggplot legend
3. correct ggtree version
4. centering things in polygons

Here's the code:

load(url("http://dl.dropbox.com/u/61803503/nycounty.RData"))
head(ny); head(key)  #view the data set from my drop box

if (!require("pacman")) install.packages("pacman")
p_load(ggplot2, ggtree, dplyr, tidyr, sp, maps, pipeR, grid, XML, gtable)

getLabelPoint <- function(county) {Polygon(county[c('long', 'lat')])@labpt}

df <- map_data('county', 'new york')                 # NY region county data
centroids <- by(df, df$subregion, getLabelPoint)     # Returns list
centroids <- do.call("rbind.data.frame", centroids)  # Convert to Data Frame
names(centroids) <- c('long', 'lat')                 # Appropriate Header

pops <-  "http://data.newsday.com/long-island/data/census/county-population-estimates-2012/" %>%
     readHTMLTable(which=1) %>%
     tbl_df() %>%
     select(1:2) %>%
     setNames(c("region", "population")) %>%
     mutate(
         population = {as.numeric(gsub("\D", "", population))},
         region = tolower(gsub("\s+[Cc]ounty|\.", "", region)),
         #weight = ((1 - (1/(1 + exp(population/sum(population)))))/11)
         weight = exp(population/sum(population)),
         weight = sqrt(weight/sum(weight))/3
     )


race_data_long <- add_rownames(centroids, "region") %>>%
    left_join({distinct(select(ny, region:other))}) %>>%
    left_join(pops) %>>%
    (~ race_data) %>>%
    gather(race, prop, white:other) %>%
    split(., .$region)

pies <- setNames(lapply(1:length(race_data_long), function(i){
    ggplot(race_data_long[[i]], aes(x=1, prop, fill=race)) +
        geom_bar(stat="identity", width=1) +
        coord_polar(theta="y") +
        theme_tree() +
        xlab(NULL) +
        ylab(NULL) +
        theme_transparent() +
        theme(plot.margin=unit(c(0,0,0,0),"mm"))
}), names(race_data_long))


e1 <- ggplot(race_data_long[[1]], aes(x=1, prop, fill=race)) +
        geom_bar(stat="identity", width=1) +
        coord_polar(theta="y")

leg1 <- gtable_filter(ggplot_gtable(ggplot_build(e1)), "guide-box")


p <- ggplot(ny, aes(long, lat, group=group)) +
    geom_polygon(colour='black', fill=NA) +
    theme_bw() +
    annotation_custom(grob = leg1, xmin = -77.5, xmax = -78.5, ymin = 44, ymax = 45)



n <- length(pies)

for (i in 1:n) {

    nms <- names(pies)[i]
    dat <- race_data[which(race_data$region == nms)[1], ]
    p <- subview(p, pies[[i]], x=unlist(dat[["long"]])[1], y=unlist(dat[["lat"]])[1], dat[["weight"]], dat[["weight"]])

}

print(p)

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