ggplot2可视化经典案例(8) 之绘制流图

相同的数据不同的展示方式，本节我们继续使用TidyTuesday 2021 第十周的项目数据集来进行数据分析

本节采用流图的方式来展示数据

安装必需R包

library(tidyverse)
library(showtext)
library(ggstream)
#  remotes::install_github("davidsjoberg/ggstream")

加载数据

tues_data <- tidytuesdayR::tt_load(2021, week = 10)

youtube <- tues_data$youtube

数据清洗及可视化

通过case_when函数更改变量的名称，并将变量转换为因子

youtube %>% 
  select(year, brand, funny:use_sex, like_count, view_count) %>% 
  pivot_longer(cols = funny:use_sex, names_to = "type") %>% 
  filter(value == T) %>% 
  mutate(type = factor(case_when(type == "animals" ~ "Contains animals",
                                 type == "celebrity" ~ "Contains celebrity",
                                 type == "danger" ~ "Contains danger",
                                 type == "funny" ~ "Contains humor",
                                 type == "patriotic" ~ "Patriotic",
                                 type == "show_product_quickly" ~ "Shows product quickly",
                                 type == "use_sex" ~ "Uses sexuality")),
         brand = ifelse(brand == "Hynudai", "Hyundai", brand),
         brand = factor(brand, levels = c("Coca-Cola", "Pepsi", "Bud Light", "Budweiser", "Doritos", "NFL", "E-Trade", "Toyota", "Hyundai", "Kia"), ordered = T)) %>% 
  group_by(year, brand, type) %>% 
  summarise(rel_likes = sum(like_count, na.rm = T)/sum(view_count, na.rm = T)) %>% 
  ggplot(aes(year, rel_likes, fill = brand)) + 
  geom_stream(extra_span = 0.1, 
              true_range = "both") + 
  coord_flip() + 
  labs(title = "Most liked Superbowl commercial types,
by brand, from 2000-2020",
       fill = "")+
  scale_x_continuous(limits = c(2000, 2020),
expand = c(0, 0), breaks = seq(2000, 2020, 1)) + 
  scale_fill_manual(values = c("#9d0208", "#dc2f02", "#f48c06", "#ffba08", "#d9ed92", "#f1faee",
"#2a9d8f", "#0077b6", "#023e8a", "#03045e")) + 
  facet_wrap(vars(type), nrow = 1) + 
  theme(panel.grid.minor = element_blank(),
        panel.grid.major.x = element_blank(),
        panel.background = element_rect(fill = NA),
        axis.title = element_blank(),
        axis.line.x = element_blank(),
        axis.text.x = element_blank(),
        axis.ticks.x = element_blank(),
        strip.background = element_rect(fill = NA),
        text = element_text(size = 15),
        legend.spacing.x = unit(0.25, "cm"),
        plot.title = element_text(face = "bold", size = 20),
        plot.margin = unit(c(1,1,1,1),"cm"))

原文链接：https://mp.weixin.qq.com/s/G0YlZjVfenuj2ww8LHmbag