R ggmap热图带值

有人能帮我看热图吗？ 我的数据：

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val\u Qtd看到你在问题中的评论，我想你会想要一张带有
val\u Qtd
的chropleth地图。我在下面解释了我的代码。我希望这对你有帮助

library(raster)
library(ggmap)

### Get data (map and polygons)
brz <- get_map('Brazil', zoom = 4)
mymap <- getData("GADM", country = "brazil", level = 1)

### I realized that a few state names were not spelled properly.
### I changed them in order to subset polygons in the following
### process.

places <- c("Distrito Federal", "Bahia", "Ceará", "Espírito Santo",
            "Minas Gerais", "Paraná", "Rio de Janeiro", "Rio Grande do Sul",
            "Santa Catarina", "São Paulo")

ds_DadosAcessos$char <- places

### Subset polygons for the states in your data. Then, convert my map
### to data frame, which is necessary for ggplot2.

mymap <- subset(mymap, NAME_1 %in% places)
temp <- fortify(mymap)

### Reorder ds_DadosAcessos by the state order in mymap
ds_DadosAcessos$order <- match(ds_DadosAcessos$char, mymap@data$NAME_1)
ds_DadosAcessos <- ds_DadosAcessos[order(ds_DadosAcessos$order), ]


### Finally, draw a map

ggmap(brz) +
geom_map(data = temp, map = temp,
         aes(x = long, y = lat, group = group, map_id = id),
         color = "black", size = 0.2) +
geom_map(data = ds_DadosAcessos, map = temp,
         aes(fill = val_Qtd, map_id = unique(temp$id)),
         alpha = 0.5) +
scale_fill_gradientn(limits = c(min(ds_DadosAcessos$val_Qtd), max(ds_DadosAcessos$val_Qtd)),
         colours = c("blue", "red") ) +
theme(legend.position = "right")

库（光栅）
图书馆（ggmap）
###获取数据（地图和多边形）
brz
库（ggmap）
图书馆（plyr）
img_Mapa快到了，我需要以热图的形式呈现，但它会很好地工作。我找到了另一种方法，我会发布解决方案。TKS！嗨，福斯托。此代码不再工作。。。请检查一下好吗？
library(ggmap)
img_Mapa <- get_map('Brazil', zoom = 4)

ggmap(img_Mapa, extent = "device") + 
      stat_density2d(data = ds_DadosAcessos, 
                     aes(x = lon, y = lat, fill = ..level.., alpha = ..level..), size = 0.01, 
                     bins = 16, geom = "polygon") + 
      scale_fill_gradient(low = "green", high = "red") + 
      scale_alpha(range = c(0, 0.3), guide = FALSE)

library(raster)
library(ggmap)

### Get data (map and polygons)
brz <- get_map('Brazil', zoom = 4)
mymap <- getData("GADM", country = "brazil", level = 1)

### I realized that a few state names were not spelled properly.
### I changed them in order to subset polygons in the following
### process.

places <- c("Distrito Federal", "Bahia", "Ceará", "Espírito Santo",
            "Minas Gerais", "Paraná", "Rio de Janeiro", "Rio Grande do Sul",
            "Santa Catarina", "São Paulo")

ds_DadosAcessos$char <- places

### Subset polygons for the states in your data. Then, convert my map
### to data frame, which is necessary for ggplot2.

mymap <- subset(mymap, NAME_1 %in% places)
temp <- fortify(mymap)

### Reorder ds_DadosAcessos by the state order in mymap
ds_DadosAcessos$order <- match(ds_DadosAcessos$char, mymap@data$NAME_1)
ds_DadosAcessos <- ds_DadosAcessos[order(ds_DadosAcessos$order), ]


### Finally, draw a map

ggmap(brz) +
geom_map(data = temp, map = temp,
         aes(x = long, y = lat, group = group, map_id = id),
         color = "black", size = 0.2) +
geom_map(data = ds_DadosAcessos, map = temp,
         aes(fill = val_Qtd, map_id = unique(temp$id)),
         alpha = 0.5) +
scale_fill_gradientn(limits = c(min(ds_DadosAcessos$val_Qtd), max(ds_DadosAcessos$val_Qtd)),
         colours = c("blue", "red") ) +
theme(legend.position = "right")

library(ggmap)
library(plyr)

img_Mapa <- get_map('Brazil', zoom = 4)

val_Qtd <- c(34, 10, 11, 7, 55, 18, 33, 16, 16, 249)
nom_State <- c("Distrito Federal","Bahia","Ceara","Espirito Santo","Minas Gerais","Parana","Rio de Janeiro","Rio Grande do Sul","Santa Catarina","Sao Paulo")
lon <- c(-47.86447, -41.70073, -39.32062, -40.30886, -44.55503, -52.02154, -43.20940, -51.21770, -50.21886, -46.62918)
lat <- c(-15.799765, -12.579738, -5.498398, -19.183423, -18.512178, -25.252089, -22.913948, -30.034632, -27.242339, -23.543179)

ds_DadosAcessos <- data.frame(char = nom_State, lon, lat, val_Qtd)

temp <- apply(ds_DadosAcessos, 1, function(x) { data.frame(lon = as.numeric(rep(x[2], log(as.numeric(x[4])))), 
                                                           lat = as.numeric(rep(x[3], log(as.numeric(x[4])))))})
heatdata2 <- ldply(temp, rbind)

ggmap(img_Mapa, extent = "device") + 
  stat_density2d(data = heatdata2, 
                 aes(x = lon, y = lat, fill = ..level.. , alpha = ..level..), 
                 geom = "polygon", position = "identity", contour = TRUE, n = 100) + 
  scale_fill_gradient(low = "green", high = "red") +            
  scale_alpha(range = c(0, 0.3), guide = FALSE)