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❝本节来介绍如何使用「sf」包来批量绘制圆形地图，主要展示如何使用分面的功能来绘制多个地图。结果仅供参考，下面小编就通过一个基础案例来进行展示，希望各位观众老爷能够喜欢。 ❞
加载R包
代码语言：javascript复制library(tidyverse)
library(maps)
library(sf)
library(tidygeocoder)
library(camcorder)
library(scico)
library(rnaturalearth)
library(terra)
library(tidyterra)
library(geodata)
构建地图数据
代码语言：javascript复制lats <- c(90:-90, -90:90, 90)
longs <- c(rep(c(180, -180), each = 181), 180)
crs_wintri <- " proj=robin lon_0=0 x_0=0 y_0=0 ellps=WGS84 datum=WGS84 units=m no_defs"
# 创建一个窗口三角形的轮廓，用于绘制地图边界
wintri_outline <-
list(cbind(longs, lats)) %>%
st_polygon() %>%
st_sfc(crs = " proj=longlat ellps=WGS84 datum=WGS84 no_defs") %>%
st_sf() %>%
lwgeom::st_transform_proj(crs = crs_wintri)
# 创建窗口三角形的经纬网格
grat_wintri <- st_graticule(lat = c(-89.9, seq(-80, 80, 20), 89.9)) %>%
lwgeom::st_transform_proj(crs = crs_wintri)
robinson <- " proj=robin lon_0=0 x_0=0 y_0=0 ellps=WGS84 datum=WGS84 units=m no_defs"
# 获取世界国家边界数据
map <- ne_countries(scale = 50, returnclass = 'sf') %>%
st_transform(graticules, crs = robinson)
g <- st_graticule(ndiscr = 500)
# 读取数据集 df
df <- read_tsv("df.xls")
绘制圆形地图
代码语言：javascript复制ggplot()
# 绘制窗口三角形轮廓
geom_sf(data = wintri_outline, fill = "white", color = NA,alpha=0.5)
# 绘制窗口三角形的经纬网格
geom_sf(data = grat_wintri, color = "grey", linewidth = 0.15)
# 绘制世界国家边界
geom_sf(data = map, size = 0.1, color = "#28282B")
# 绘制六边形图层，用于展示数据分布
geom_hex(data = df %>% drop_na(), aes(x = longitude, y = latitude),
binwidth = c(2.5, 2.5), color = "grey96", linewidth = .01)
# 设置填充颜色的渐变和标签
scale_fill_gradient2(midpoint = 1000, labels = scales::comma,
guide = guide_colorbar(
title = "x......x",
title.position = "left",
title.theme = element_text(angle = 90),
barwidth = unit(.75, "lines"),
barheight = unit(10, "lines")))
scale_x_continuous(expand = c(0,0))
scale_y_continuous(expand = c(0,0))
facet_wrap2(vars(day_part))
theme_minimal()
theme(panel.grid = element_blank(),
axis.title = element_blank(),
axis.text = element_blank(),
panel.spacing = unit(1.5, "lines"),
strip.text = element_text(face = "bold", hjust = 0,size = 11),
plot.background = element_rect(fill = "grey96", color = NA),
plot.margin = margin(0.1,0.1,0.1,0.1))
