194-花花看了一眼，其中就一张不会画

Jun 6, 2020 5 min read cnposts

刘小泽写于2020.6.6 偶然在网上看到一个人分享的ggplot2作图技巧：https://cedricscherer.netlify.app/2019/05/17/the-evolution-of-a-ggplot-ep.-1/#data

先上图！

上数据！

准备两个文件即可：

然后数据生成脚本在：https://gist.github.com/Z3tt/301bb0c7e3565111770121af2bd60c11

我们主要利用：region和student_ratio 这两列数据，并根据student_ratio得到中位数student_ratio_region

画图

图一：最简单的箱线图

library(tidyverse)

ggplot(df_ratios, aes(x = region, y = student_ratio)) +
  geom_boxplot()

图二：将中位数降序排列

也就是把student_ratio_region降序

df_sorted <- df_ratios %>%
  mutate(region = fct_reorder(region, -student_ratio_region))

ggplot(df_sorted, aes(x = region, y = student_ratio)) +
  geom_boxplot()

图三：将x、y轴翻转，并在坐标轴上加上0 => coord_flip

看到之前的y轴没有起始坐标，于是可以人为定义

ggplot(df_sorted, aes(x = region, y = student_ratio)) +
  geom_boxplot() +
  coord_flip() +
  scale_y_continuous(limits = c(0, 90))

图四：自定义设置主题 => 全局theme_set/ 局部theme

theme_set(theme_light(base_size = 15, base_family = "Arial"))

这个主题是全局设置的，以后画的各种图都是theme_light形式，除非自己再特定修改某个图的主题，例如下面增加主题设置：

# 把数据先做成一个gg对象，之后画各种图都是在这个对象的基础上
g <- ggplot(df_sorted, aes(x = region, y = student_ratio, color = region)) +
    coord_flip() +
    scale_y_continuous(limits = c(0, 90), expand = c(0.005, 0.005)) +
    scale_color_uchicago() + # ggsci包的配色方案
    labs(x = NULL, y = "Student to teacher ratio") +
    theme(legend.position = "none",
          axis.title = element_text(family = "Times New Roman",size = 12), # 特定设置文体格式
          axis.text.x = element_text(family = "Times New Roman", size = 10),
          panel.grid = element_blank())

能清楚看到，设置后y轴是一种字体（theme_set设置的），x轴axis.text.x和整图的标题axis.title是另一种字体【这里只作为解释，后面还是使用统一的Arial字体】

现在看上去是空白，其实数据已经存到对象中了，我们要做的就是把数据映射到某种类型的可视化中（比如箱线图、散点图等）

图五：设置透明 => alpha

g + geom_point(size = 3, alpha = 0.15)

图六：图形叠加

比如要在上面散点图的基础上，增加箱线图，并且去掉离群点

【注意观察：下面两行的不同】

一个是先画点图，一个是先画箱线图。可以看到图B是我们更想看到的，因为ggplot2是图层叠加，先画的放在下面，于是先画箱线图

# A
g + geom_point(size = 3, alpha = 0.15)+
    geom_boxplot(color = "gray60", outlier.alpha = 0) 
# B
g + geom_boxplot(color = "gray60", outlier.alpha = 0) +
    geom_point(size = 3, alpha = 0.15)
# outlier.alpha = 0设置比较巧妙，如果存在离群点，就设置透明度为0，也就是看不到了；另外，还可以通过设置形状：outlier.shape = NA 来去除

图七：如何让散点真的散开 => geom_jitter

之前的散点图还是存在点的重叠，如果要分开，就要添加“抖动（jitter）”

set.seed(123) # 这个添加抖动是随机的，因此需要设置随机种子
g + geom_jitter(size = 2, alpha = 0.25, width = 0.2) #width参数可以自己修改看看变化

图八：在散点图上添加统计结果 => stat_summary

比如添加均值（以点显示）

g +
  geom_jitter(size = 2, alpha = 0.25, width = 0.2) +
  stat_summary(fun.y = mean, geom = "point", size = 5)

每个组添加完均值后，再添加一个整体的均值（用一条线表示）

# 求出整体的均值
world_avg <- df_ratios %>%
  summarize(avg = mean(student_ratio, na.rm = T)) %>%
  pull(avg)

# 加一条竖线
g +
  geom_hline(aes(yintercept = world_avg), color = "gray70", size = 0.6) +
  stat_summary(fun.y = mean, geom = "point", size = 5) +
  geom_jitter(size = 2, alpha = 0.25, width = 0.2)

将每组的均值与整体均连接起来 => geom_segment (segment表示线段)

g +
    geom_jitter(size = 2, alpha = 0.25, width = 0.2) +
    stat_summary(fun.y = mean, geom = "point", size = 5)+
    geom_hline(aes(yintercept = world_avg), color = "gray70", size = 0.6)+
    geom_segment(aes(x = region, xend = region,
                     y = world_avg, yend = student_ratio_region),
                 size = 0.8)

从上面geom_segment代码就能看到，分别设置了起始和终止。另外这里的x不是指横坐标，而是指当时生成gg对象时设置的x（即region）【如下图】

图九：添加文字 => annotate

可以设置文字内容、位置、字体、字号、颜色

g_text = g +
    geom_jitter(size = 2, alpha = 0.25, width = 0.2) +
    stat_summary(fun.y = mean, geom = "point", size = 5)+
    geom_hline(aes(yintercept = world_avg), color = "gray70", size = 0.6)+
    geom_segment(aes(x = region, xend = region,
                     y = world_avg, yend = student_ratio_region),
                 size = 0.8) +
    annotate("text", x = 6.3, y = 35, family = "Arial", size = 2.7, color = "gray20",
             label = paste0("Worldwide average:\n",round(world_avg, 1)," students per teacher")) +
    annotate("text", x = 3.5, y = 10, family = "Arial", size = 2.7, color = "gray20",
             label = "Continental average") +
    annotate("text", x = 1.7, y = 11, family = "Arial", size = 2.7, color = "gray20",
             label = "Countries per continent") +
    annotate("text", x = 1.9, y = 64, family = "Arial", size = 2.7, color = "gray20",
             label = "The Central African Republic has by far\nthe most students per teacher")

图十：添加箭头 => geom_curve

这个过程需要不断调整，如果嫌麻烦可以后期自己加上

分别设定箭头的起始（x、y）和终止（xend、yend），以及曲率curvature

arrows <- tibble(
  x1 = c(6, 3.65, 1.8, 1.8, 1.8),
  x2 = c(5.6, 4, 2.07, 2.78, 1.08),
  y1 = c(world_avg + 6, 10.5, 9, 9, 76),
  y2 = c(world_avg + 0.1, 18.4, 14.48, 12, 83.41195)
)

(g_arrows <- g_text +
  geom_curve(data = arrows, aes(x = x1, y = y1, xend = x2, yend = y2),
             arrow = arrow(length = unit(0.08, "inch")), size = 0.5,
             color = "gray20", curvature = -0.3))

图十一：马赛克图 => geom_tile

感觉会了这个图，就会了乐高拼图除了知道使用geom_tile，还要设置合适的背景才能出来效果

# 如果只用简单的geom_tile
df_sorted %>%
        ggplot(aes(x = x, y = y, fill = region, color = region)) +
        geom_tile(color = "white")

# 还需要做：
# 1.将纵坐标降序排列：scale_y_reverse()
# 2.配色：scale_fill_uchicago(guide = F) 
# 3. 确保两个轴上相等的长度表示相同的单位变化：coord_equal()
# 4. 设置各种透明背景：theme()
(map_regions <- df_sorted %>%
  ggplot(aes(x = x, y = y, fill = region, color = region)) +
    geom_tile(color = "white") +
    scale_y_reverse() +
    scale_fill_uchicago(guide = F) +
    coord_equal() +
    theme(line = element_blank(),
          panel.background = element_rect(fill = "transparent"),
          plot.background = element_rect(fill = "transparent",
                                         color = "transparent"),
          panel.border = element_rect(color = "transparent"),
          strip.background = element_rect(color = "gray20"),
          axis.text = element_blank(),
          plot.margin = margin(0, 0, 0, 0)) +
    labs(x = NULL, y = NULL))

最后

如果要把马赛克图加到原来的图中

g_arrows +
  annotation_custom(ggplotGrob(map_regions), xmin = 2.5, xmax = 7.5, ymin = 55, ymax = 85)

ggplot2