所有作品合集传送门： Tidy Tuesday

2018 年合集传送门： 2018

Comic book characters

欢迎来到ggplot2的世界！

ggplot2是一个用来绘制统计图形的 R 软件包。它可以绘制出很多精美的图形，同时能避免诸多的繁琐细节，例如添加图例等。

用 ggplot2 绘制图形时，图形的每个部分可以依次进行构建，之后还可以进行编辑。ggplot2 精心挑选了一系列的预设图形，因此在大部分情形下可以快速地绘制出许多高质量的图形。如果在格式上还有额外的需求，也可以利用 ggplot2 中的主题系统来进行定制, 无需花费太多时间来调整图形的外观，而可以更加专注地用图形来展现你的数据。

1. 一些环境设置

# 设置为国内镜像, 方便快速安装模块
options("repos" = c(CRAN = "https://mirrors.tuna.tsinghua.edu.cn/CRAN/"))

2. 设置工作路径

wkdir <- '/home/user/R_workdir/TidyTuesday/2018/2018-05-29_Comic_book_characters/src-c'
setwd(wkdir)

3. 加载 R 包

library(tidyverse)

# 导入字体设置包
library(showtext)
# font_add_google() showtext 中从谷歌字体下载并导入字体的函数
# name 中的是字体名称, 用于检索, 必须严格对应想要字体的名字
# family 后面的是代码后面引用时的名称, 自己随便起
# 需要能访问 Google, 也可以注释掉下面这行, 影响不大
# font_families_google() 列出所有支持的字体, 支持的汉字不多
# http://www.googlefonts.net/
font_add_google(name = "Karantina", family =  "ka")
font_add_google(name = "Cutive", family = "albert")
font_add_google(name = "ZCOOL XiaoWei", family = "zxw")

# 后面字体均可以使用导入的字体
showtext_auto()

4. 加载数据

df_input <- readr::read_csv("../data/week9_comic_characters.csv", show_col_types = FALSE)

# 简要查看数据内容
glimpse(df_input)

## Rows: 23,272
## Columns: 17
## $ ...1             <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16…
## $ publisher        <chr> "Marvel", "Marvel", "Marvel", "Marvel", "Marvel", "Ma…
## $ page_id          <dbl> 1678, 7139, 64786, 1868, 2460, 2458, 2166, 1833, 2948…
## $ name             <chr> "Spider-Man (Peter Parker)", "Captain America (Steven…
## $ urlslug          <chr> "\\/Spider-Man_(Peter_Parker)", "\\/Captain_America_(…
## $ id               <chr> "Secret Identity", "Public Identity", "Public Identit…
## $ align            <chr> "Good Characters", "Good Characters", NA, "Good Chara…
## $ eye              <chr> "Hazel Eyes", "Blue Eyes", "Blue Eyes", "Blue Eyes", …
## $ hair             <chr> "Brown Hair", "White Hair", "Black Hair", "Black Hair…
## $ sex              <chr> "Male Characters", "Male Characters", "Male Character…
## $ gsm              <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ alive            <chr> "Living Characters", "Living Characters", "Living Cha…
## $ appearances      <dbl> 4043, 3360, 3061, 2961, 2258, 2255, 2072, 2017, 1955,…
## $ first_appearance <chr> "1962, August", "1941, March", "1974, October", "1963…
## $ month            <chr> "August", "March", "October", "March", "November", "N…
## $ year             <dbl> 1962, 1941, 1974, 1963, 1950, 1961, 1961, 1962, 1963,…
## $ date             <date> 1962-08-01, 1941-03-01, 1974-10-01, 1963-03-01, 1950…

# 检查数据的列名
colnames(df_input)

##  [1] "...1"             "publisher"        "page_id"          "name"            
##  [5] "urlslug"          "id"               "align"            "eye"             
##  [9] "hair"             "sex"              "gsm"              "alive"           
## [13] "appearances"      "first_appearance" "month"            "year"            
## [17] "date"

5. 数据预处理

publisher. = c("DC电影宇宙",  "漫威漫画公司")
df_albert <- df_input %>% 
  # group_by() 以指定的列进行分组
  group_by(publisher, year) %>% 
  # summarise() 用于对数据进行统计描述, 这里根据上一步分组进行计数
  summarise(count = n()) %>% 
  # ungroup() 取消分组
  ungroup() %>% 
  # 因子化 publisher 列
  mutate(publisher = factor(publisher, labels = publisher.))

# 去除缺失值
df_plot <- na.omit(df_albert)

# 简要查看数据内容
glimpse(df_plot)

## Rows: 154
## Columns: 3
## $ publisher <fct> DC电影宇宙, DC电影宇宙, DC电影宇宙, DC电影宇宙, DC电影宇宙, …
## $ year      <dbl> 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, …
## $ count     <int> 1, 9, 4, 10, 18, 64, 61, 52, 14, 15, 7, 9, 20, 20, 6, 9, 12,…

6. 利用 ggplot2 绘图

# PS: 方便讲解, 我这里进行了拆解, 具体使用时可以组合在一起
gg <- df_plot %>% ggplot(aes(x = year, y = count, fill = publisher))
gg <- gg + geom_bar(stat = "identity")
# scale_x_continuous() 对连续变量设置坐标轴显示范围
gg <- gg + scale_x_continuous(labels = c(1940, "'60", "'80", 2000), breaks = seq(1940, 2000, 20)) 
# scale_y_continuous() 对连续变量设置坐标轴显示范围
gg <- gg + scale_y_continuous(labels = seq(0, 500, 100), breaks = seq(0, 500, 100))
# scale_fill_manual() 采取的是手动赋值的方法, 也就是直接把颜色序列赋值给它的参数 value
gg <- gg + scale_fill_manual(values = c("#0000FF", "#FF0000"))
# labs() 对图形添加注释和标签（包含标题 title、子标题 subtitle、坐标轴 x & y 和引用 caption 等注释)
gg <- gg + labs(title = "每年推出的新漫画书人物数量 (1936-2013)",
                subtitle = NULL,
                x = NULL,
                y = NULL,
                caption = "资料来源: FiveThirtyEight.com · graph by 萤火之森 · 2022-10-17")
# theme_minimal() 去坐标轴边框的最小化主题
gg <- gg + theme_minimal()
# theme() 实现对非数据元素的调整, 对结果进行进一步渲染, 使之更加美观
gg <- gg + theme(
  # panel.border 面板背景 数据上面
  panel.border = element_blank(),
  # plot.background 图片背景 
  plot.background = element_blank(),
  # plot.margin 调整图像边距, 上-右-下-左
  plot.margin = margin(12, 10, 2, 15), 
  # plot.title 主标题
  plot.title = element_text(hjust = 0., color = "black", size = 32, face = "bold", family = 'zxw'),
  # plot.subtitle 次要标题
  plot.subtitle = element_text(hjust = 0., color = "black", size = 24, face = "bold"),
  # strip.text.x 自定义分面图每个分面标题的文字
  strip.text.x = element_text(size = 24, hjust = 0.5, face = "bold", family = 'zxw', color = 'red'),
  # text 设置文本格式
  text = element_text(size = 18, hjust = 0, face = "bold", color = 'black'),
  # axis.text 坐标轴刻度文本
  axis.text = element_text(size = 24, hjust = 0, face = "bold", color = 'black', family = 'ka'),
  # legend.direction 设置图例的方向, horizontal 表示水平方向摆放
  legend.direction = 'horizontal',
  # legend.title 设置图例标题
  legend.title = element_blank(),
  # legend.position 设置图例位置, "none" 表示不显示图例
  legend.position = 'none')

7. 保存图片到 PDF 和 PNG

gg + theme(legend.position = c(0.31234, 0.834))

filename = '20180529-C-01'
ggsave(filename = paste0(filename, ".pdf"), width = 11.2, height = 6.2, device = cairo_pdf)
ggsave(filename = paste0(filename, ".png"), width = 11.2, height = 6.2, dpi = 100, device = "png", bg = 'white')

gg + facet_wrap(~ publisher)

filename = '20180529-C-02'
ggsave(filename = paste0(filename, ".pdf"), width = 11.2, height = 6.2, device = cairo_pdf)
ggsave(filename = paste0(filename, ".png"), width = 11.2, height = 6.2, dpi = 100, device = "png", bg = 'white')

8. session-info

sessionInfo()

## R version 4.2.1 (2022-06-23)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.5 LTS
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/liblapack.so.3
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] showtext_0.9-5  showtextdb_3.0  sysfonts_0.8.8  forcats_0.5.2  
##  [5] stringr_1.4.1   dplyr_1.0.10    purrr_0.3.4     readr_2.1.2    
##  [9] tidyr_1.2.1     tibble_3.1.8    ggplot2_3.3.6   tidyverse_1.3.2
## 
## loaded via a namespace (and not attached):
##  [1] lubridate_1.8.0     assertthat_0.2.1    digest_0.6.29      
##  [4] utf8_1.2.2          R6_2.5.1            cellranger_1.1.0   
##  [7] backports_1.4.1     reprex_2.0.2        evaluate_0.16      
## [10] highr_0.9           httr_1.4.4          pillar_1.8.1       
## [13] rlang_1.0.6         curl_4.3.2          googlesheets4_1.0.1
## [16] readxl_1.4.1        rstudioapi_0.14     jquerylib_0.1.4    
## [19] rmarkdown_2.16      textshaping_0.3.6   googledrive_2.0.0  
## [22] bit_4.0.4           munsell_0.5.0       broom_1.0.1        
## [25] compiler_4.2.1      modelr_0.1.9        xfun_0.32          
## [28] systemfonts_1.0.4   pkgconfig_2.0.3     htmltools_0.5.3    
## [31] tidyselect_1.1.2    fansi_1.0.3         crayon_1.5.1       
## [34] tzdb_0.3.0          dbplyr_2.2.1        withr_2.5.0        
## [37] grid_4.2.1          jsonlite_1.8.2      gtable_0.3.1       
## [40] lifecycle_1.0.3     DBI_1.1.3           magrittr_2.0.3     
## [43] scales_1.2.1        vroom_1.5.7         cli_3.4.1          
## [46] stringi_1.7.8       cachem_1.0.6        farver_2.1.1       
## [49] fs_1.5.2            xml2_1.3.3          bslib_0.4.0        
## [52] ragg_1.2.3          ellipsis_0.3.2      generics_0.1.3     
## [55] vctrs_0.4.2         tools_4.2.1         bit64_4.0.5        
## [58] glue_1.6.2          hms_1.1.2           parallel_4.2.1     
## [61] fastmap_1.1.0       yaml_2.3.5          colorspace_2.0-3   
## [64] gargle_1.2.1        rvest_1.0.3         knitr_1.40         
## [67] haven_2.5.1         sass_0.4.2

测试数据

配套数据下载：Comic book characters