ggplot2

数据可视化工具

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1 教科书和资料

1.1 ggplot2: Elegant Graphics for Data Analysis (3e)

https://ggplot2-book.org/

1.2 Top 50 ggplot2 Visualizations - The Master List (With Full R Code)

https://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html

1.3 教学课件：Introduction to GGPlot2 in R

https://docs.google.com/presentation/d/1X-TjuIRGZwkj1Ob0g7sVTBsx5HJeQmpSL66ceuL9lXU/edit#slide=id.p

##　安装和调用

只需要安装一次，但是每次重新启动R后使用ggplot2，需要重新调用

# install.packages("ggplot2")

你可以直接调用 ggplot2，你也可以通过调用 tidyverse 来使用 ggplot2，我一般直接调用tidyverse，以便同时使用dplyr和tidyr等工具。

# library(ggplot2)
library(tidyverse) # 

2 演示数据

调用 tidyverse后，可以直接使用R的许多内置数据。这里我们用mpg作演示。

str(mpg) # 先看看数据结构

tibble [234 × 11] (S3: tbl_df/tbl/data.frame)
 $ manufacturer: chr [1:234] "audi" "audi" "audi" "audi" ...
 $ model       : chr [1:234] "a4" "a4" "a4" "a4" ...
 $ displ       : num [1:234] 1.8 1.8 2 2 2.8 2.8 3.1 1.8 1.8 2 ...
 $ year        : int [1:234] 1999 1999 2008 2008 1999 1999 2008 1999 1999 2008 ...
 $ cyl         : int [1:234] 4 4 4 4 6 6 6 4 4 4 ...
 $ trans       : chr [1:234] "auto(l5)" "manual(m5)" "manual(m6)" "auto(av)" ...
 $ drv         : chr [1:234] "f" "f" "f" "f" ...
 $ cty         : int [1:234] 18 21 20 21 16 18 18 18 16 20 ...
 $ hwy         : int [1:234] 29 29 31 30 26 26 27 26 25 28 ...
 $ fl          : chr [1:234] "p" "p" "p" "p" ...
 $ class       : chr [1:234] "compact" "compact" "compact" "compact" ...

mpg$cyl

  [1] 4 4 4 4 6 6 6 4 4 4 4 6 6 6 6 6 6 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 4 4 6 6 6
 [38] 4 6 6 6 6 6 6 6 6 6 6 6 6 6 6 8 8 8 8 8 6 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
 [75] 8 8 8 6 6 6 6 8 8 6 6 8 8 8 8 8 6 6 6 6 8 8 8 8 8 4 4 4 4 4 4 4 4 4 4 4 4
[112] 4 6 6 6 4 4 4 4 6 6 6 6 6 6 8 8 8 8 8 8 8 8 8 8 8 8 6 6 8 8 4 4 4 4 6 6 6
[149] 6 6 6 6 6 8 6 6 6 6 8 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6 6 6 8 4 4 4 4 6 6
[186] 6 4 4 4 4 6 6 6 4 4 4 4 4 8 8 4 4 4 6 6 6 6 4 4 4 4 6 4 4 4 4 4 5 5 6 6 4
[223] 4 4 4 5 5 4 4 4 4 6 6 6

mpg %>% 
  select(cyl)

# A tibble: 234 × 1
     cyl
   <int>
 1     4
 2     4
 3     4
 4     4
 5     6
 6     6
 7     6
 8     4
 9     4
10     4
# ℹ 224 more rows

print(mpg) # same to mpg

# A tibble: 234 × 11
   manufacturer model      displ  year   cyl trans drv     cty   hwy fl    class
   <chr>        <chr>      <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
 1 audi         a4           1.8  1999     4 auto… f        18    29 p     comp…
 2 audi         a4           1.8  1999     4 manu… f        21    29 p     comp…
 3 audi         a4           2    2008     4 manu… f        20    31 p     comp…
 4 audi         a4           2    2008     4 auto… f        21    30 p     comp…
 5 audi         a4           2.8  1999     6 auto… f        16    26 p     comp…
 6 audi         a4           2.8  1999     6 manu… f        18    26 p     comp…
 7 audi         a4           3.1  2008     6 auto… f        18    27 p     comp…
 8 audi         a4 quattro   1.8  1999     4 manu… 4        18    26 p     comp…
 9 audi         a4 quattro   1.8  1999     4 auto… 4        16    25 p     comp…
10 audi         a4 quattro   2    2008     4 manu… 4        20    28 p     comp…
# ℹ 224 more rows

3 ggplot2 的两个基本语法

3.1 先来看一个离散图

ggplot(mpg, aes(x = displ, y = hwy)) +
  geom_point()

但我更倾向于用 %>%

mpg %>%
  ggplot(aes(x = displ  , y = hwy)) + # 这样写代码，会有变量名的提示，既快又不容易输错
  geom_point()

4 bbplot

pacman::p_load_gh("bbc/bbplot")
library(gapminder)
line_df <- gapminder %>% 
  filter(country=="China") %>% 
  ggplot(aes(x=year,y=lifeExp))+
  geom_line(colour="skyblue",linewidth=1)+
  geom_hline(yintercept = 0,linewidth=1,colour="purple")+
  labs(title="Living longer",
       subtitle="Life expectancy in China 1952-2007")+
  bbc_style()

line_df

5 How to add annotations to ggplots in R

set.seed(1)
p <- trees %>% 
  slice_sample(n=5) %>% 
  ggplot(aes(x=Girth,y=Height))+
  geom_point()

p

p+  annotate(geom = "text",
           x=16.3,
           y=76.5,
           label = "Outlier")

p+
  annotate(geom = "label",
           x=14,
           y = 71.5,
           label = "Outlier")+
  annotate(geom = "segment",
           x = 14, 
           y = 72,
           xend = 16.1,
           yend = 76.5,
           arrow = arrow())+
  annotate(geom = "rect",
           xmin = 8,
           xmax = 11.5,
           ymin = 64.5,
           ymax = 72.5,
           alpha = 0.15,
           color = "skyblue",
           fill = "pink")