[GBD数据库挖掘] 14.ggplot2优雅展示预期寿命数据

R语言数据分析指南

发布于 2023-12-13 15:58:27

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发布于 2023-12-13 15:58:27

加载R包

library(tidyverse)
library(stringr)
library(reshape2)
library(ggtext)
library(ggh4x)

导入数据

life_expectancy <- read_csv("life_expectancy.csv")

数据清洗

df <- life_expectancy %>% filter(Entity %in% c("Asia","Europe","Africa","Oceania","United States",
                                              "High-income countries",
                                              "Middle-income countries","Lower-middle-income countries",
                                              "Low-income countries","World")) %>% 
  select(-Code) %>% 
  pivot_wider(names_from = "Entity",values_from = "LifeExpectancy") %>% 
  melt(id.vars = c("Year", "World"),
       variable.factor = FALSE, value.factor = FALSE,
       variable.name = "Entity", value.name = "LifeExpectancy")

df2 = df %>% dplyr::rename("Entity2"="Entity")

数据可视化

ggplot(data = df) +
  geom_line(data = df2, aes(Year, LifeExpectancy, group = Entity2),color = "grey85", linewidth = .65) +
  geom_line(aes(Year, LifeExpectancy, group = Entity, color = "Entity"),linewidth = .65) +
  geom_line(aes(Year, World, group = 1, color = "World"),linewidth = .65) +
  scale_color_manual(values = c("World"  = "#0064ee", "Entity" = "#ee1300")) +
  scale_x_continuous(limits = c(1950, 2021), expand = c(0, 0), breaks = seq(1950, 2021, by = 20)) +
  facet_wrap2(vars(Entity), ncol = 3, axes = "all") +
  theme_minimal() +
  theme(
    legend.position = "bottom",
    legend.justification = "left",
    legend.title = element_blank(),
    strip.text = element_text(face = "bold", hjust = 0.5, size = 10),
    panel.spacing = unit(1.5, "lines"),
    panel.grid.major = element_line(linetype = "dashed", linewidth = .35, color = "grey85"),
    panel.grid.minor = element_line(linetype = "dashed", linewidth = .25, color = "grey85"),
    axis.ticks.y = element_line(linewidth = .35, color = "grey85"),
    axis.title.x = element_blank(),
    axis.title.y = element_text(hjust = 0.5, margin = margin(r = 10)),
    axis.text.x = element_text(size = 8),
    plot.background = element_rect(fill = "#f5f5f5", color = NA),
    plot.margin = margin(10, 10, 10, 10))