ggplot2轻松绘制令人惊艳的地图

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本节来介绍如何使用「ggplot2」绘制「2020美国大选地图」，本文由「RGzxs」投稿，小编进行了简单排版，下面来看实际操作

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加载R包

my_packages <- c("tidyverse", "broom", "coefplot", "cowplot",
                 "gapminder", "GGally", "ggrepel", "ggridges", "gridExtra",
                 "here", "interplot", "margins", "maps", "mapproj",
                 "mapdata", "MASS", "quantreg", "rlang", "scales",
                 "survey", "srvyr", "viridis", "viridisLite", "devtools","ggplot2",
                 "ggthemes")
for (package in my_packages) {
  if (!require(package,character.only=T, quietly=T)) {
    install.packages(package)
    library(package, character.only=T)
  }
}

绘制美国各州地图

加载数据，选择几列并随机选择几行

load("election.rda")
election %>% select(state,total_vote,
                    r_points,pct_trump,party,census) %>% 
  sample_n(5)
party_colors <- c("#2E74C0", "#CB454A")

绘制基础地图

us_states <- map_data("state")
head(us_states)
p <- ggplot(data = us_states,
            mapping = aes(x = long, y = lat,
                          group = group))

p + geom_polygon(fill = "white", color = "black")

以region为填充

p <- ggplot(data = us_states,
            aes(x = long, y = lat,
                group = group, fill = region))

p + geom_polygon(color = "gray90", size = 0.1) + guides(fill = FALSE)

将投影设置为Albers

p <- ggplot(data = us_states,
            mapping = aes(x = long, y = lat,
                          group = group, fill = region))

p + geom_polygon(color = "gray90", size = 0.1) +
    coord_map(projection = "albers", lat0 = 39, lat1 = 45) +
    guides(fill = FALSE)

将2020年美国大选结果添加到地图上

election$region <- tolower(election$state)
us_states_elec <- left_join(us_states, election)
p <- ggplot(data = us_states_elec,
            aes(x = long, y = lat,
                group = group, fill = party))

p + geom_polygon(color = "gray90", size = 0.1) +
    coord_map(projection = "albers", lat0 = 39, lat1 = 45)

添加题目，将图例移到下面，修改颜色

p0 <- ggplot(data = us_states_elec,
             mapping = aes(x = long, y = lat,
                           group = group, fill = party))
p1 <- p0 + geom_polygon(color = "gray90", size = 0.1) +
    coord_map(projection = "albers", lat0 = 39, lat1 = 45) 
p2 <- p1 + scale_fill_manual(values = party_colors) +
    labs(title = "Election Results 2016", fill = NULL)
p2 + theme_map()

映射连续变量-川普的选票

p0 <- ggplot(data = us_states_elec,
             mapping = aes(x = long, y = lat,
                           group = group, fill = pct_trump))
p1 <- p0 + geom_polygon() +
  coord_map(projection = "albers", lat0 = 39, lat1 = 45) 
p2 <- p1+scale_fill_gradient(low = "white", high = "#CB454A")+
  labs(title = "Trump vote")
p2 + theme_map() +labs(fill="Percent")

等值线图（ur-choropleths）

加载数据

load("county_data.rda")

load("county_map.rda")
county_map %>% sample_n(5)
county_data %>% select(
  id,name,state,pop_dens,pct_black) %>% 
  sample_n(5)

合并

county_full <- left_join(county_map,county_data,by="id")

绘制每平方英里中的人口密度图

p <- ggplot(data = county_full,
            mapping = aes(x = long, y = lat,
                          fill = pop_dens, 
                          group = group))

p1 <- p + geom_polygon() + coord_equal()

p2 <- p1 + scale_fill_brewer(palette="Blues",
                             labels = c("0-10", "10-50", "50-100", "100-500",
                                        "500-1,000", "1,000-5,000", ">5,000"))

p2 + labs(fill = "Population per\nsquare mile") +
  theme_map() +
  guides(fill = guide_legend(nrow = 1)) + 
  theme(legend.position = "bottom")

• 参考资料：Data Visualization 作者：Kieran Healy 链接：https://socviz.co/index.html#preface

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