R的世界地图？

时间：2013-11-19 18:33:06

标签： r

我有一个数组，告诉我每个国家的观察数量。

countries <- structure(c(532L, 3L, 1L, 15L, 1L, 1L, 2L, 3L, 16L, 2L, 43L, 
1L, 2L, 2L, 1L, 1L, 1L, 3L, 2L, 1L, 4L, 4L, 16L, 13L, 2L, 2L, 
9L, 1L, 1L, 5L, 3L, 5L, 1L, 1L, 3L, 1L, 10L, 11L, 4L, 2L, 1L, 
7L, 1L, 2L, 6L, 7L, 1L, 6L, 1L, 2L, 7L, 1L, 20L, 1L, 2L, 1L, 
3L, 2L, 5L, 76L, 2L, 1L, 1L), .Dim = 63L, .Dimnames = structure(list(
    c("United States", "Argentina", "Armenia", "Australia", "Austria", 
    "Bangladesh", "Belarus", "Belgium", "Brazil", "Bulgaria", 
    "Canada", "Chile", "China", "Colombia", "Croatia", "Cuba", 
    "Cyprus", "Czech Republic", "Dominican Republic", "Ecuador", 
    "Estonia", "France", "Germany", "Greece", "Guatemala", "Hong Kong", 
    "India", "Indonesia", "Iran", "Ireland", "Israel", "Italy", 
    "Kazakhstan", "Kenya", "Latvia", "Malaysia", "Mexico", "Netherlands", 
    "New Zealand", "Norway", "Peru", "Philippines", "Poland", 
    "Portugal", "Romania", "Russia", "Saudi Arabia", "Serbia", 
    "Singapore", "Slovakia", "South Africa", "South Korea", "Spain", 
    "Sri Lanka", "Sweden", "Switzerland", "Thailand", "Turkey", 
    "Ukraine", "United Kingdom", "Uruguay", "Uzbekistan", "Venezuela"
    )), .Names = ""))

我可以使用地图库绘制地图。但我很感激帮助它让它看起来更好。

library(maps)
map(database="world")
map(database="world", col=countries, fil=countries)
legend("topleft", fill = countries, legend = countries, col = countries)
box()

第一个大问题是传说。连续比例可能看起来比每个国家的一种颜色更好，不知道如何做到这一点。在确定之后，任何可以做到让它看起来更好的东西将非常感激。

谢谢！

我可以使用googleVis制作动态地图，但是我在制作使用ggplot2的静态地图时遇到了麻烦。例如，使用ggplot2看起来我在美国没有人。

这是我的代码

#Load My data
countries <- structure(list(country = c("United States", "Afghanistan", "Albania", 
                                        "Argentina", "Armenia", "Australia", "Austria", "Bahrain", "Bangladesh", 
                                        "Belarus", "Belgium", "Bosnia and Herzegovina", "Brazil", "Bulgaria", 
                                        "Canada", "Chile", "China", "Colombia", "Croatia", "Cuba", "Cyprus", 
                                        "Czech Republic", "Denmark", "Dominican Republic", "Ecuador", 
                                        "Egypt", "El Salvador", "Estonia", "Finland", "France", "Germany", 
                                        "Greece", "Guatemala", "Haiti", "Hong Kong", "Hungary", "Iceland", 
                                        "India", "Indonesia", "Iran", "Ireland", "Israel", "Italy", "Japan", 
                                        "Jordan", "Kazakhstan", "Kenya", "Korea, South", "Latvia", "Libya", 
                                        "Lithuania", "Macedonia", "Malaysia", "Malta", "Mexico", "Moldova", 
                                        "Morocco", "Netherlands", "New Zealand", "Nicaragua", "Niger", 
                                        "Nigeria", "Norway", "Pakistan", "Panama", "Peru", "Philippines", 
                                        "Poland", "Portugal", "Romania", "Russia", "Saudi Arabia", "Serbia", 
                                        "Singapore", "Slovakia", "Slovenia", "Somalia", "South Africa", 
                                        "South Korea", "Spain", "Sri Lanka", "Sweden", "Switzerland", 
                                        "Taiwan", "Thailand", "Turkey", "Ukraine", "United Arab Emirates", 
                                        "United Kingdom", "Uruguay", "Uzbekistan", "Venezuela", "Zimbabwe"
), count = c(1224L, 1L, 1L, 4L, 2L, 40L, 2L, 1L, 2L, 5L, 8L, 
             2L, 40L, 3L, 106L, 4L, 16L, 10L, 8L, 4L, 2L, 5L, 4L, 5L, 3L, 
             1L, 2L, 5L, 1L, 10L, 26L, 41L, 3L, 1L, 3L, 2L, 1L, 34L, 2L, 3L, 
             10L, 4L, 19L, 1L, 1L, 1L, 1L, 1L, 4L, 1L, 3L, 1L, 2L, 2L, 36L, 
             1L, 1L, 31L, 10L, 1L, 1L, 1L, 2L, 6L, 2L, 3L, 29L, 7L, 11L, 13L, 
             21L, 5L, 9L, 6L, 3L, 2L, 1L, 22L, 2L, 42L, 1L, 3L, 5L, 2L, 6L, 
             5L, 13L, 2L, 157L, 4L, 1L, 5L, 1L)), .Names = c("country", "count"
             ), row.names = c(NA, -93L), class = "data.frame")

#Make dynamic map
library(googleVis)
# Make the map!
geoMap <- gvisGeoMap(countries, locationvar="country", numvar="count",
                     options=list(dataMode="regions"))
plot(geoMap)

#Make ggplot2 map
library(maps)
library(ggplot2)
#load world data
world <- map_data("world")

#Delete Antarctica
world <- subset(world,region!="Antarctica")
#Add count
world$count<-countries$count[match(world$region,countries$country,nomatch=NA)]
qplot(long, lat, data = world, group = group, fill=count, geom ="polygon",ylab="",xlab="")

为什么ggplot2地图错了？我该如何解决？

谢谢！

2 个答案:

答案 0 :(得分：4)

这可能不是您想要的，但这是使用googleVis包的解决方案。

# I had to change your data a little bit
countries2 <- data.frame(country=names(countries), count=as.integer(countries), 
                         stringsAsFactors=FALSE)

# Install the googleVis package and load it
# install.packages("googleVis")
library(googleVis)

# Make the map!
geoMap <- gvisGeoMap(countries2, locationvar="country", numvar="count",
                 options=list(dataMode="regions"))
plot(geoMap)

这将生成您的数据的交互式Geo Map，当您将鼠标悬停在不同区域时，它应突出显示该数据并显示计数的弹出窗口。

（道歉 - 这个问题只是尝试这个套餐的借口:)。 ）

如果你想要一个静态情节，我也可以尝试制作它。

答案 1 :(得分：0)

这是我的解决方案。 

#Load My data
countries <- structure(list(country = c("United States", "Afghanistan", "Albania", 
                                        "Argentina", "Armenia", "Australia", "Austria", "Bahrain", "Bangladesh", 
                                        "Belarus", "Belgium", "Bosnia and Herzegovina", "Brazil", "Bulgaria", 
                                        "Canada", "Chile", "China", "Colombia", "Croatia", "Cuba", "Cyprus", 
                                        "Czech Republic", "Denmark", "Dominican Republic", "Ecuador", 
                                        "Egypt", "El Salvador", "Estonia", "Finland", "France", "Germany", 
                                        "Greece", "Guatemala", "Haiti", "Hong Kong", "Hungary", "Iceland", 
                                        "India", "Indonesia", "Iran", "Ireland", "Israel", "Italy", "Japan", 
                                        "Jordan", "Kazakhstan", "Kenya", "Korea, South", "Latvia", "Libya", 
                                        "Lithuania", "Macedonia", "Malaysia", "Malta", "Mexico", "Moldova", 
                                        "Morocco", "Netherlands", "New Zealand", "Nicaragua", "Niger", 
                                        "Nigeria", "Norway", "Pakistan", "Panama", "Peru", "Philippines", 
                                        "Poland", "Portugal", "Romania", "Russia", "Saudi Arabia", "Serbia", 
                                        "Singapore", "Slovakia", "Slovenia", "Somalia", "South Africa", 
                                        "South Korea", "Spain", "Sri Lanka", "Sweden", "Switzerland", 
                                        "Taiwan", "Thailand", "Turkey", "Ukraine", "United Arab Emirates", 
                                        "United Kingdom", "Uruguay", "Uzbekistan", "Venezuela", "Zimbabwe"
), count = c(1224L, 1L, 1L, 4L, 2L, 40L, 2L, 1L, 2L, 5L, 8L, 
             2L, 40L, 3L, 106L, 4L, 16L, 10L, 8L, 4L, 2L, 5L, 4L, 5L, 3L, 
             1L, 2L, 5L, 1L, 10L, 26L, 41L, 3L, 1L, 3L, 2L, 1L, 34L, 2L, 3L, 
             10L, 4L, 19L, 1L, 1L, 1L, 1L, 1L, 4L, 1L, 3L, 1L, 2L, 2L, 36L, 
             1L, 1L, 31L, 10L, 1L, 1L, 1L, 2L, 6L, 2L, 3L, 29L, 7L, 11L, 13L, 
             21L, 5L, 9L, 6L, 3L, 2L, 1L, 22L, 2L, 42L, 1L, 3L, 5L, 2L, 6L, 
             5L, 13L, 2L, 157L, 4L, 1L, 5L, 1L)), .Names = c("country", "count"
             ), row.names = c(NA, -93L), class = "data.frame")

suppressPackageStartupMessages({
  library(maptools)
  library(ggplot2)
})



PolygonCoords <- function(polygon) {
  polygons <- polygon@Polygons
  coords.list <- lapply(seq_along(polygons), function(i) {
    # Extract the group, sequence, area, longitude, and latitude.
    coords <- polygons[[i]]@coords
    cbind(i, 1:nrow(coords), polygons[[i]]@area, coords)
  })
  coords.df <- as.data.frame(do.call(rbind, coords.list))
  names(coords.df) <- c("order", "seq", "area", "long", "lat")
  return(coords.df)
}

ConvertWorldSimple <- function(mapdata, min.area = 0) {

  # min.area is the minimum size of the polygons. Setting to some
  # positive value will filter out tiny islands.


  coords.list <- lapply(mapdata@polygons, PolygonCoords)
  ncoords <- sapply(coords.list, nrow)
  coords.df <- do.call(rbind, coords.list)
  coords.df$country <- rep(mapdata@data$NAME, ncoords)
  country.group <- factor(paste(coords.df$country, coords.df$order))
  coords.df$group <- as.numeric(country.group)
  coords.df <- coords.df[coords.df$area >= min.area, ]
  return(coords.df)
}

data("wrld_simpl")
world <- ConvertWorldSimple(wrld_simpl, min.area = 0.1)
#Delete Antarctica
world <- subset(world,country!="Antarctica")

#Add count
world$count<-countries$count[match(world$country,countries$country,nomatch=NA)]
x<-quantile(world$count, na.rm=TRUE)
qplot(long, lat, data = world, group = group, fill=count, geom ="polygon",ylab="",xlab="") + 
  scale_fill_gradient(name="log(Number of\nStudents)", trans = "log")

感谢您的帮助！

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