传单渲染不正确的国家

Question

我正在尝试使用 leaflet 绘制几个国家/地区，但它显示的国家/地区不正确。以下是我的最小可重现示例：

library(leaflet)
library(maps)


  df <- data.frame(name = c("Afghanistan", "Albania" , "Algeria" , "Armenia"),
                   code = c("AFG", "ALB", "DZA", "ARM"),
                    val = c(5, 10, 15, 20), stringsAsFactors = FALSE)

  pal <- colorNumeric(
    palette = "Blues",
    domain = as.numeric(df$val))

  labels <- sprintf(
    "<strong>Country:%s</strong><br/>Value:%g /",
    df$name, df$val)%>% lapply(htmltools::HTML) 

  Country = map("world", fill = TRUE, plot = FALSE, regions=iso.expand(df$code,regex = TRUE))

  leaflet(Country) %>% addTiles() %>%
    addPolygons(fillOpacity = 0.6,  smoothFactor = 0.5, stroke = TRUE, weight = 1, 
                color = ~pal(as.numeric(df$val)),
                label = labels)

我收到以下传单：

如您所见，阿尔及利亚显示为阿尔巴尼亚。如果我从我的数据中删除亚美尼亚并绘制传单，我会得到正确的位置。以下是它的代码和图像。

library(leaflet)
  library(maps)

  df <- data.frame(name = c("Afghanistan", "Albania" , "Algeria" ),
                   code = c("AFG", "ALB", "DZA"),
                    val = c(5, 10, 15), stringsAsFactors = FALSE)

  pal <- colorNumeric(
    palette = "Blues",
    domain = as.numeric(df$val))

  labels <- sprintf(
    "<strong>Country:%s</strong><br/>Value:%g /",
    df$name, df$val)%>% lapply(htmltools::HTML) 

  Country = map("world", fill = TRUE, plot = FALSE, regions=iso.expand(df$code,regex = TRUE))

  leaflet(Country) %>% addTiles() %>%
    addPolygons(fillOpacity = 0.6,  smoothFactor = 0.5, stroke = TRUE, weight = 1, 
                color = ~pal(as.numeric(df$val)),
                label = labels)

我错过了什么吗？

Answer 1

我认为这个问题与map 对象中的多边形顺序有关（如果您设置了label = Country$names，标签现在是正确的）。无论如何，您可以通过将Country 转换为SpatialPolygons 对象来解决问题（参见here）。

library(maptools)
IDs <- sapply(strsplit(Country$names, ":"), function(x) x[1])
Country <- map2SpatialPolygons(Country, 
                               IDs=IDs, 
                               proj4string=CRS("+proj=longlat +datum=WGS84"))

leaflet(Country) %>% addTiles() %>%
  addPolygons(fillOpacity = 0.6,  smoothFactor = 0.5, stroke = TRUE, weight = 1, 
              color = pal(as.numeric(df$val)),
              label = labels)