[GBD数据库挖掘] 15.地图展示不同年份间人均预期寿命差异

R语言数据分析指南

发布于 2023-12-14 14:51:57

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代码可运行

加载R包

library(tidyverse)
library(sf)
library(camcorder)
library(MetBrewer)
# install.packages("giscoR")
library(giscoR)

R包版本

导入数据

life_df <- read_csv('data.csv') %>% janitor::clean_names()

数据清洗

le_change <- life_df %>% 
  group_by(entity) %>% 
  filter(year == 2021 | year ==1995) %>% 
  filter(!is.na(code)) %>% 
  pivot_wider(names_from = year, values_from = c(life_expectancy0,
                                                 life_expectancy10, 
                                                 life_expectancy25, 
                                                 life_expectancy45, 
                                                 life_expectancy65, 
                                                 life_expectancy80)) %>% 
  pivot_longer(`Life expectancy at age 0`:`At age 80`, names_to = "age", values_to = "change") %>% 
  mutate(age = fct_inorder(age))

获取地图数据

world <- giscoR::gisco_get_countries() %>% 
  janitor::clean_names() %>% 
  rename(code = iso3_code) %>% 
  st_transform(crs = "+proj=moll")

world_le_2021 <- world %>% left_join(le_change) %>% 
  filter(!is.na(change))

数据可视化

ggplot(world_le_2021) +
  geom_sf(aes(fill = change), linewidth = 0.05, color = "black") +
  scale_fill_gradientn(colors=rev(met.brewer("Cassatt1")))+
  facet_wrap(vars(age), ncol = 2) +
  guides(fill = guide_colorsteps(title.position = "top", show.limits = TRUE)) +
  theme_minimal() +
  theme(
    legend.position = "top",
    legend.title = element_text(hjust = 0.5),
    legend.key.width = unit(3, "lines"),
    legend.key.height = unit(0.6, "lines"),
    plot.background = element_rect(fill = "grey99", color = NA),
    strip.text = element_text(size = 12),
    axis.text = element_blank(),
    panel.grid = element_line(linewidth = 0.1, color = "grey70"),
    plot.margin = margin(10, 10, 10, 10))