ggmap具有值的熱圖

Question

任何人都可以使用ggmap（heatmap）來幫助我嗎？ 我的數據：

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) 

我的情節：

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) 

顯然，熱圖使用記錄的數量calc下熱圖。但是我需要通過val_Qtd列來計算熱圖。

也許是這樣的。

Answer 1

看到在你的問題你的意見，我想您一定想用val_Qtd一個chropleth地圖。我在下面解釋了我的代碼。我希望這能幫到您。

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") 

Answer 2

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)