结合ggplot和ggmap中的choropleth [英] Combining choropleth made in ggplot and ggmap

问题描述

使用ggplot2创建了

我还使用ggmap创建了一个道路地图。这里是代码：

pre $ map< - get_map（location = c（lon = mean（mapdata $ lon），lat = mean （mapdata $ lat））
，zoom = 10
，maptype =roadmap
，color =bw）
p < - ggmap（map）+
scale_x_continuous（limits = c（min（mapdata $ lon），max（mapdata $ lon）），expand = c（0,0））+
scale_y_continuous（limits = c（min（mapdata $ lat），max （mapdata $ lat）），expand = c（0,0））
p


这里是它生成的地图。

当我尝试合并他们虽然我得到一个错误。这里是我用来将它们和错误结合起来的代码：

  okc < -  okc + p 
 
错误p + o：二元运算符的非数字参数
另外：警告消息：
+$不兼容的方法（+ .gg，Ops.data.frame）
  

我不知道为什么我会收到此错误。是否因为地图缩放不一样？除了使用非常不精确的缩放功能外，我无法想象如何缩放ggmap。
如果任何人有任何关于如何在ggmap之上分层的想法，我将非常感谢。

以下是其余代码重新创建ggplot choropleth。

  library（acs）
 library（ggplot2）
 library（ggmap）
库（UScensus2010）
库（RColorBrewer）
库（dplyr）
库（比例）
 
 #http：//api.census.gov/data/ key_signup.html 
 api.key.install（key =c369cd6ed053a84332caa62301eb8afe98bed825）
 
＃在形状文件中加载（您需要从人口普查下载此文件）
＃ ftp://ftp2.census.gov/geo/tiger/TIGER2013/TRACT/tl_2013_40_tract.zip 
 
 ##加载，子集shapefile 
 geodat< -readShapePoly（insert shapefile here， proj4string = CRS（'+ proj = longlat + datum = NAD83'））
 geodat< -geodat [geodat $ COUNTYFP == 109，] 
 
 ##强化ggplot消化
 geodat.f< -fortify（geodat，region =GEOID）
 
＃美国社区调查数据：OK人口普查区域的中位HH收入
 ok.counties = geo.make（state =OK，county =Oklahoma，tract =*）
 ok.income< -acs.fetch（geography = ok.counties，table.number =B19013，endyear = 2013）
 
 
＃合并数据集
 geo_dat< -geography（ok.income）
 var_dat< -as.data.frame（估计（ok.income））
 acs_data< -cbind（geo_dat，var_dat）
 acs_data $ id< - 粘贴（40109，acs_data $ tract，sep =）
 
 ## from dplyr 
 mapdata< -left_join（geodat.f，acs_data）
 
 okc < -  ggplot（）+ 
 geom_polygon（data = mapdata，aes（x = long，y = lat，group = group，$ b $ fill = B19013_001），color =black，size = 0.5）+ 
 scale_fill_distiller（palette =Reds，labels = comma，
 breaks = pretty_breaks（n = 10），values = c（1,0））+ 
 guides（fill = guide_legend（reverse = TRUE））+ 
 theme_nothing（legend = TRUE）+ 
 ggtitle（'OKC'Map）
  

解决方案

这实际上在Leaflet中做得好得多。

  library（leaflet）
 library（rgdal）
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 addTiles％>％
 addPolygons（stroke = T，fillOpacity = .5，smoothFactor = .5，color =〜pal（B19013_001））％>％
 addLegend（bottomright，pal = pal，values =〜B19013_001，title =Legend Title，opacity = .8）
  

通过用addProviderTiles（CartoDB.Positron）替换addTiles命令来更改底部映射。您可以在 https：//rstudio.github上看到其他选项和更多信息。 io / leaflet / basemaps.html

Created a choropleth using ggplot2. Here's the ggplot code

okc <- ggplot() +
  geom_polygon(data = mapdata, aes(x = long, y = lat, group = group,
                                   fill = B19013_001), color = "black", size = 0.5)+
  scale_fill_distiller(palette = "Reds", labels = comma,
                       breaks = pretty_breaks(n = 10), values = c(1,0)) +
  guides(fill = guide_legend(reverse = TRUE)) +
  theme_nothing(legend = TRUE) +
  ggtitle('Map of 40109') 

Here's a sample of the data from mapdata:

       long      lat order  hole piece         group          id
1 -97.54285 35.51951     1 FALSE     1 40109100100.1 40109100100
2 -97.54282 35.51954     2 FALSE     1 40109100100.1 40109100100
3 -97.54280 35.51963     3 FALSE     1 40109100100.1 40109100100
4 -97.54276 35.51976     4 FALSE     1 40109100100.1 40109100100
5 -97.54270 35.51993     5 FALSE     1 40109100100.1 40109100100
6 -97.54266 35.52016     6 FALSE     1 40109100100.1 40109100100
                                          NAME state county  tract B19013_001
1 Census Tract 1001, Oklahoma County, Oklahoma    40    109 100100      33440
2 Census Tract 1001, Oklahoma County, Oklahoma    40    109 100100      33440
3 Census Tract 1001, Oklahoma County, Oklahoma    40    109 100100      33440
4 Census Tract 1001, Oklahoma County, Oklahoma    40    109 100100      33440
5 Census Tract 1001, Oklahoma County, Oklahoma    40    109 100100      33440
6 Census Tract 1001, Oklahoma County, Oklahoma    40    109 100100      33440

It produced this plot.

I also created a roadway map using ggmap. Here's the code:

map <- get_map(location = c(lon = mean(mapdata$lon), lat = mean(mapdata$lat))
               , zoom = 10
               , maptype = "roadmap"
               , color = "bw")
p <- ggmap(map) +
  scale_x_continuous(limits = c(min(mapdata$lon), max(mapdata$lon)), expand = c(0, 0)) +
  scale_y_continuous(limits = c(min(mapdata$lat), max(mapdata$lat)), expand = c(0, 0))
p

And here's the map it produces.

When I try to combine them though I get an error. Here's the code I use to combine them and the error:

okc <- okc + p

Error in p + o : non-numeric argument to binary operator
In addition: Warning message:
Incompatible methods ("+.gg", "Ops.data.frame") for "+"

I'm not sure why I'm getting this error. Is it because the maps are not scaled the same? I could not figure how else to scale ggmap other than using the very imprecise zoom function. If anyone has any ideas about how to layer the choropleth on top of the ggmap I will be very thankful.

Here's the rest of the code to recreate the ggplot choropleth.

    library(acs)
    library(ggplot2)
    library(ggmap)
    library(UScensus2010)
    library(RColorBrewer)
    library(dplyr)
    library(scales)

    #http://api.census.gov/data/key_signup.html
    api.key.install(key="c369cd6ed053a84332caa62301eb8afe98bed825")

    # Load in Shape File (You'll need to download this file from the census)
    #ftp://ftp2.census.gov/geo/tiger/TIGER2013/TRACT/tl_2013_40_tract.zip

    ## load, subset shapefile
    geodat<-readShapePoly("insert shapefile here", proj4string=CRS('+proj=longlat +datum=NAD83'))
    geodat<-geodat[geodat$COUNTYFP==109,]

    ## fortify for ggplot digestion
    geodat.f<-fortify(geodat,region="GEOID")

    # American Community Survey Data: Median HH Income for OK Census Tracts
    ok.counties=geo.make(state="OK", county="Oklahoma", tract="*")
    ok.income<-acs.fetch(geography=ok.counties, table.number="B19013", endyear=2013)


    # Merge Data Sets 
    geo_dat<-geography(ok.income)
    var_dat<-as.data.frame(estimate(ok.income))
    acs_data<-cbind(geo_dat,var_dat)
    acs_data$id<- paste("40109", acs_data$tract, sep = "")

    ## from dplyr
    mapdata<-left_join(geodat.f,acs_data)

    okc <- ggplot() +
      geom_polygon(data = mapdata, aes(x = long, y = lat, group = group,
                                       fill = B19013_001), color = "black", size = 0.5)+
      scale_fill_distiller(palette = "Reds", labels = comma,
                           breaks = pretty_breaks(n = 10), values = c(1,0)) +
      guides(fill = guide_legend(reverse = TRUE)) +
      theme_nothing(legend = TRUE) +
      ggtitle('Map of OKC')

解决方案

This is actually much better done in Leaflet. It looks better aesthetically and also code wise it is more intuitive.

library(leaflet)
library(rgdal)
library(RColorBrewer)

pal <- colorNumeric("OrRd", domain = new$pct_minority_popn)

leaflet(mapdata) %>%
 addTiles %>%
 addPolygons(stroke=T, fillOpacity=.5, smoothFactor=.5, color=~pal(B19013_001)) %>%
 addLegend("bottomright", pal=pal, values=~B19013_001, title="Legend Title", opacity=.8)

You can change the bottom map by replacing the addTiles command with something like addProviderTiles("CartoDB.Positron"). You can see the rest of the options and more info on leaflet at: https://rstudio.github.io/leaflet/basemaps.html

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