我感兴趣的是绘制艾姆斯数据集中邻域的多边形/凸船体表示，类似于O 'Reilly版本的Tidy-modeling with R中使用的方法。
看起来，同一段落的第4章有两个不同的图像，这取决于您使用的来源，第一个图像来自here的O 'Reilly版本，第二个来自tmwr.org
x1c 0d1x的数据

就个人而言，我更喜欢第一个，因为它更容易看到相邻区域的重叠。Tmwr.org有一个GitHub repo，但是凸船体代码没有在那里捕获。
从他们的仓库中，我可以看到他们从this网站下载了一个形状文件，并将其用于背景中的道路Map，然后覆盖多边形。
我试图创建多边形，并使用谷歌Map作为背景，但我没有太大的成功添加谷歌Map层。
在代码的底部，我可以绘制谷歌Map层，但当我引入ames_sf时，我得到以下错误：

Error in `geom_sf()`:
! Problem while computing aesthetics.
ℹ Error occurred in the 4th layer.
Caused by error:
! object 'lon' not found

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从我用ggplot生成的凸包和谷歌Map图像可以看出，他们使用了不同的坐标值，这可能是问题所在。我很困惑，因为在第46行ames_sf是用crs = 3857定义的，然后在第90行的底部ggmap(map)被传递给coord_sf，其中st_crs也被设置为3857。
下面是我拼凑的代码（其中一些来自here），目前我正在寻找一些帮助，在googleMap的背景分层。任何可以分享的帮助将不胜感激。

# LOAD THE REQUIRED LIBRARIES
pacman::p_load(sf, ggplot2, dplyr, RColorBrewer, AmesHousing)

# ASSIGN A PALETTE OF 8 COLORS FROM THE 'DARK2' PALETTE TO A VARIABLE
col_vals <- brewer.pal(8, "Dark2")

# CREATE A NAMED VECTOR 'ames_cols' WITH NEIGHBORHOOD NAMES MAPPED TO SPECIFIC COLORS FROM 'col_vals'
# COPIED FROM THE TMWR.ORG REPO
ames_cols <- c(
  North_Ames = col_vals[3],
  College_Creek = col_vals[4],
  Old_Town = col_vals[8],
  Edwards = col_vals[5],
  Somerset = col_vals[8],
  Northridge_Heights = col_vals[4],
  Gilbert = col_vals[2],
  Sawyer = col_vals[7],
  Northwest_Ames = col_vals[6],
  Sawyer_West = col_vals[8],
  Mitchell = col_vals[3],
  Brookside = col_vals[1],
  Crawford = col_vals[4],
  Iowa_DOT_and_Rail_Road = col_vals[2],
  Timberland = col_vals[2],
  Northridge = col_vals[1],
  Stone_Brook = col_vals[5],
  South_and_West_of_Iowa_State_University = col_vals[3],
  Clear_Creek = col_vals[1],
  Meadow_Village = col_vals[1],
  Briardale = col_vals[7],
  Bloomington_Heights = col_vals[1],
  Veenker = col_vals[2],
  Northpark_Villa = col_vals[2],
  Blueste = col_vals[5],
  Greens = col_vals[6],
  Green_Hills = col_vals[8],
  Landmark = col_vals[3],
  Hayden_Lake = "red" # 'Hayden_Lake' SPECIFICALLY ASSIGNED THE COLOR RED
)

# LOAD AND PREPARE THE AMES HOUSING DATA
ames_data <- make_ames() %>%
  janitor::clean_names()

# CONVERT AMES DATA INTO AN SF (SIMPLE FEATURES) OBJECT FOR SPATIAL ANALYSIS AND
# TRANSFORM EPSG 3857 (Pseudo-Mercator, what Google uses)
ames_sf <- st_as_sf(ames_data, coords = c("longitude", "latitude"), crs = 3857)

# CREATE POLYGONS FOR EACH NEIGHBORHOOD BY AGGREGATING POINTS INTO A CONVEX HULL
ames_sf <- ames_sf %>%
  group_by(neighborhood) %>%
  summarize() %>%
  st_convex_hull()

# PLOT THE CONVEX HULLS USING GGPLOT
#ggplot(data = ames_sf) +
#  geom_sf(aes(fill = neighborhood), color = "white", size = 0.5) +
#  scale_fill_manual(values = ames_cols) +
#  theme_minimal() +
#  labs(title = 'Neighborhoods in Ames') +
#  theme(legend.position = "none")

map <- get_map("Ames, Iowa", maptype = "roadmap", zoom = "auto", scale = "auto", source = "google")

# Define a function to fix the bbox to be in EPSG:3857
ggmap_bbox <- function(map) {
  if (!inherits(map, "ggmap")) stop("map must be a ggmap object")
  # Extract the bounding box (in lat/lon) from the ggmap to a numeric vector,
  # and set the names to what sf::st_bbox expects:
  map_bbox <- setNames(
    unlist(attr(map, "bb")),
    c("ymin", "xmin", "ymax", "xmax")
  )

  # Coonvert the bbox to an sf polygon, transform it to 3857,
  # and convert back to a bbox (convoluted, but it works)
  bbox_3857 <- st_bbox(st_transform(st_as_sfc(st_bbox(map_bbox, crs = 4326)), 3857))

  # Overwrite the bbox of the ggmap object with the transformed coordinates
  attr(map, "bb")$ll.lat <- bbox_3857["ymin"]
  attr(map, "bb")$ll.lon <- bbox_3857["xmin"]
  attr(map, "bb")$ur.lat <- bbox_3857["ymax"]
  attr(map, "bb")$ur.lon <- bbox_3857["xmax"]
  map
}

# Use the function:
map <- ggmap_bbox(map)

ggmap(map) +
  coord_sf(crs = st_crs(3857)) + # force the ggplot2 map to be in 3857
  geom_sf(data = ames_sf, aes(fill = neighborhood), color = "white", size = 0.5, alpha = 0.5)

型
使用ggmaps我可以创建多边形并将它们打印到坐标网格中，但我很难添加到Map背景中。