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❝本节来介绍如何使用「ggplot2」来绘制年龄分布金子塔图，下面小编就通过一个案例来进行展示数据为随意构建无实际意义仅作图形展示用，希望各位观众老爷能够喜欢，「数据+代码已经上传2023VIP群，加群的观众老爷请自行下载」。
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加载R包
library(tidyverse)
library(ggtext)
library(patchwork)
library(showtext)
导入数据
age_gaps <- readr::read_csv('age_gaps.txt')
数据清洗
act1_m <- age_gaps %>% filter(character_1_gender == "man") %>% pull(actor_1_age)
act2_m <- age_gaps %>% filter(character_2_gender == "man") %>% pull(actor_2_age)
act1_w <- age_gaps %>% filter(character_1_gender == "woman") %>% pull(actor_1_age)
act2_w <- age_gaps %>% filter(character_2_gender == "woman") %>% pull(actor_2_age)
ages_m <- c(act1_m, act2_m)
ages_w <- c(act1_w, act2_w)
构建绘图数据
ages_m_bins <- tibble(age = ages_m) %>%
mutate(bin = cut(ages_m, breaks = seq(0, 85, 5),
include.lowest = TRUE, right = FALSE)) %>%
count(bin) %>%
complete(bin, fill = list(n = 0)) %>% select(ages = bin, men = n)
ages_w_bins <- tibble(age = ages_w) %>%
mutate(bin = cut(ages_w, breaks = seq(0, 85, 5),
include.lowest = TRUE, right = FALSE)) %>%
count(bin) %>%
complete(bin, fill = list(n = 0)) %>% select(ages = bin, women = n)
ages_bins <- ages_m_bins %>%
left_join(ages_w_bins) %>%
mutate(ages_labels = c("0 - 4","5 - 9","10 - 14","15 - 19","20 - 24","25 - 29",
"30 - 34","35 - 39","40 - 44","45 - 49","50 - 54","55 - 59",
"60 - 64","65 - 69","70 - 74", "75 - 79", "80+")) %>%
rowid_to_column()
数据可视化
ggplot(data = ages_bins) +
geom_rect(aes(xmin = -men - 25,xmax = -25, ymin = rowid - 0.4, ymax = rowid + 0.4),
fill="#0487e2") +
geom_rect(aes(xmin = 25,xmax = women + 25, ymin = rowid - 0.4, ymax = rowid + 0.4),
fill="#ed2939") +
geom_text(aes(x=0, y = rowid,family = "Roboto Condensed",
label = ages_labels),color = "white", size =5) +
scale_x_continuous(breaks = c(seq(-375, -25, 50), seq(25, 375, 50)),
labels = c(abs(seq(-350, 0, 50)), seq(0, 350, 50)),
limits = c(-375, 375)) +
labs(x=NULL,y=NULL)+
theme_minimal() +
theme(
panel.background = element_rect(fill = "#1a1a1a", color = NA),
panel.grid.minor = element_blank(),
panel.grid.major.y = element_blank(),
panel.grid.major.x = element_line(linewidth = 0.15, linetype = "dotted"),
plot.background = element_rect(fill = "#1a1a1a", color = NA),
axis.text.y = element_blank(),
axis.text.x = element_text(family = "Roboto Condensed",color = "white", size = 15))
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