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量化金融与金融编程

L02 ggplot2 数据可视化 | 课前预习


曾永艺

厦门大学管理学院


2023-09-18

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一图胜千言

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ggplot2v3.4.3 快速入门

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1 The Layered Grammar of Graphics

Data Visualization：将数据映射为几何对象的美学属性

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1 The Layered Grammar of Graphics

Data Visualization：将数据映射为几何对象的美学属性

  • 数据（data）：我们想要可视化的对象，包含变量
  • 几何对象（geometries)：用来呈现数据的几何图形对象，如点、条形、线条等
  • 美学属性（aesthetic）：几何对象的视觉属性，如x坐标和y坐标位置、颜色、形状等
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1 The Layered Grammar of Graphics

Data Visualization：将数据映射为几何对象的美学属性

  • 数据（data）：我们想要可视化的对象，包含变量
  • 几何对象（geometries)：用来呈现数据的几何图形对象，如点、条形、线条等
  • 美学属性（aesthetic）：几何对象的视觉属性，如x坐标和y坐标位置、颜色、形状等

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1 The Layered Grammar of Graphics

ggplot2 的语法模板

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1 The Layered Grammar of Graphics

ggplot2 的语法模板

ggplot(data = <DATA>) +
  <GEOM_FUNCTION>(
     mapping = aes(<MAPPINGS>),
     stat = <STAT>, 
     position = <POSITION>
  ) +
  <COORDINATE_FUNCTION> +
  <FACET_FUNCTION>
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2 将数据映射为几何对象的美学属性

library(tidyverse)
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2 将数据映射为几何对象的美学属性

library(tidyverse)
mpg  # print(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(l5)   f        18    29 p     compact
#> 2 audi         a4      1.8  1999     4 manual(m5) f        21    29 p     compact
#> 3 audi         a4      2    2008     4 manual(m6) f        20    31 p     compact
#> # ℹ 231 more rows
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2 将数据映射为几何对象的美学属性

library(tidyverse)
mpg  # print(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(l5)   f        18    29 p     compact
#> 2 audi         a4      1.8  1999     4 manual(m5) f        21    29 p     compact
#> 3 audi         a4      2    2008     4 manual(m6) f        20    31 p     compact
#> # ℹ 231 more rows
# 查看ggplot2包内置数据集mpg的帮助文档
?mpg  # help(mpg)
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2 将数据映射为几何对象的美学属性

library(tidyverse)
mpg  # print(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(l5)   f        18    29 p     compact
#> 2 audi         a4      1.8  1999     4 manual(m5) f        21    29 p     compact
#> 3 audi         a4      2    2008     4 manual(m6) f        20    31 p     compact
#> # ℹ 231 more rows
# 查看ggplot2包内置数据集mpg的帮助文档
?mpg  # help(mpg)
  1. displ: a car's engine size, in litres.
  2. hwy: a car's fuel efficiency on the highway, in miles per gallon (mpg).
  3. class: "type" of car
    ...
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2 将数据映射为几何对象的美学属性

ggplot()

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2 将数据映射为几何对象的美学属性

ggplot(data = mpg)                           # 数据集

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2 将数据映射为几何对象的美学属性

ggplot(data = mpg,                           # 数据集
       mapping = aes(x = displ, y = hwy))    # 映射：变量 -> x坐标和y坐标

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2 将数据映射为几何对象的美学属性

ggplot(data = mpg,                           # 数据集
       mapping = aes(x = displ, y = hwy)) +  # 映射：变量 -> x坐标和y坐标
  geom_point()                               # 几何对象

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2 将数据映射为几何对象的美学属性

ggplot(data = mpg) + 
  geom_point(
    mapping = aes(x = displ, y = hwy, colour = class)  # 3个映射
  )

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2 将数据映射为几何对象的美学属性

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy, shape = class))
#> Warning: The shape palette can deal with a maximum of 6 discrete values because more than
#> 6 becomes difficult to discriminate; you have 7. Consider specifying shapes
#> manually if you must have them.
#> Warning: Removed 62 rows containing missing values (`geom_point()`).

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2 将数据映射为几何对象的美学属性

  • R内置有25个形状（shape），在ggplot2中可用名字或数字进行设定

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2 将数据映射为几何对象的美学属性

  • R内置有25个形状（shape），在ggplot2中可用名字或数字进行设定

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2 将数据映射为几何对象的美学属性

  • R内置有25个形状（shape），在ggplot2中可用名字或数字进行设定

  • 设定图形属性相关的说明文档 vignette("ggplot2-specs")
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2 将数据映射为几何对象的美学属性

ggplot(data = mpg) + 
  geom_point(
    mapping = aes(x = displ, y = hwy), 
    shape = "triangle", size = 3, colour = "red", alpha = 0.3
    # 变量无关（“大家都一样”，即非映射）的几何对象图形属性应在aes()外进行设定
  )

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2 将数据映射为几何对象的美学属性

# layered!
ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy)) +
  geom_smooth(mapping = aes(x = displ, y = hwy))  # layered!

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2 将数据映射为几何对象的美学属性

ggplot(
  data = mpg,
  mapping = aes(x = displ, y = hwy)  # 共用映射，提前至ggplot()中
) +
  geom_point() +
  geom_smooth()

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2 将数据映射为几何对象的美学属性

ggplot(mpg, aes(displ, hwy)) +       # 省略常用参数名
  geom_point(aes(colour = class)) +  # 图层自用映射
  geom_smooth(data = filter(mpg, class == "pickup"))  # 不同的数据集

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3 统计变换、位置调整、坐标、分面

ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut))
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3 统计变换、位置调整、坐标、分面

ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut))

Where comes the "count" in y-axis? 😅

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3 统计变换、位置调整、坐标、分面

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3 统计变换、位置调整、坐标、分面

下面的代码会得到和使用 geom_bar() 相同的结果

ggplot(data = diamonds) + 
  stat_count(mapping = aes(x = cut))
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3 统计变换、位置调整、坐标、分面

ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut, 
                         y = after_stat(prop),   # ?aes_eval
                         group = 1))             # ?aes_group_order

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3 统计变换、位置调整、坐标、分面

ggplot(data = diamonds %>% group_by(cut) %>% count()) +  # 数据分组汇总计算
  geom_bar(
    mapping = aes(x = cut, y = n),
    stat = "identity"
  )

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3 统计变换、位置调整、坐标、分面

ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut, fill = clarity))
# geom_bar()默认的position = "stack"

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3 统计变换、位置调整、坐标、分面

ggplot(data = diamonds) + 
  geom_bar(
    mapping = aes(x = cut, fill = clarity),
    position = "dodge"  # position = position_dodge(width = 0.9)
  )

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3 统计变换、位置调整、坐标、分面

ggplot(data = mpg) + 
  geom_point(
    mapping = aes(x = displ, y = hwy),
    position = "jitter"   # same as `ggplot() + geom_jitter()`
  )

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3 统计变换、位置调整、坐标、分面

ggplot(data = mpg, mapping = aes(x = class, y = hwy)) + 
  geom_boxplot() +
  coord_flip()  # ggplot2 3.3.0后直接调换x，y参数即可

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3 统计变换、位置调整、坐标、分面

bar <- ggplot(data = diamonds) +  # 将图形对象存为变量bar，可在Environment标签页中检查其内容
  geom_bar(
    mapping = aes(x = cut, fill = cut), show.legend = FALSE, width = 1
  ) + 
  theme(aspect.ratio = 1) + labs(x = NULL, y = NULL)
bar + coord_polar()

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3 统计变换、位置调整、坐标、分面

ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) + 
  geom_point(data = mutate(mpg, class = NULL), colour = "grey") +
  geom_point() + 
  facet_wrap(vars(class), nrow = 2) # facet_wrap(~ class, nrow = 2)

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3 统计变换、位置调整、坐标、分面

ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) + 
  geom_point(data = transform(mpg, cyl = NULL), colour = "grey") +
  geom_point() + 
  facet_grid(rows = vars(drv), cols = vars(cyl))  # facet_grid(drv ~ cyl)

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4 标签、标注、标度、主题等

ggplot(mpg, aes(displ, hwy)) +
  geom_point(aes(colour = class)) +
  geom_smooth(se = FALSE) +
  labs(  # 标题、小标题等
    title = "Fuel efficiency",
    subtitle = "... generally decreases with engine size",
    caption = "Data from fueleconomy.gov"
  )

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4 标签、标注、标度、主题等

ggplot(mpg, aes(displ, hwy)) +
  geom_point(aes(colour = class)) +
  geom_smooth(se = FALSE) +
  labs( # 图形属性 = 标签
    x = "Engine displacement (L)",
    y = "Highway fuel economy (mpg)",
    colour = "Car type"
  )

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4 标签、标注、标度、主题等

# 生成辅助数据集
best <- mpg %>%
  group_by(class) %>%
  filter(row_number(desc(hwy)) == 1)
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4 标签、标注、标度、主题等

# 生成辅助数据集
best <- mpg %>%
  group_by(class) %>%
  filter(row_number(desc(hwy)) == 1)
ggplot(mpg, aes(displ, hwy)) +
  geom_point(aes(colour = class)) +
  geom_text(
    aes(label = model), 
    data = best
  )

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4 标签、标注、标度、主题等

# 生成辅助数据集
best <- mpg %>%
  group_by(class) %>%
  filter(row_number(desc(hwy)) == 1)
ggplot(mpg, aes(displ, hwy)) +
  geom_point(aes(colour = class)) +
  geom_text(
    aes(label = model), 
    data = best
  )

ggplot(mpg, aes(displ, hwy)) +
  geom_point(aes(colour = class)) +
  geom_label(
    aes(label = model), data = best, 
    nudge_y = 2, alpha = 0.5
  )

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4 标签、标注、标度、主题等

ggplot(mpg, aes(displ, hwy)) +
  geom_point(aes(colour = class)) +
  geom_point(size = 3, shape = 1, data = best) +
  ggrepel::geom_label_repel(aes(label = model), data = best)  # install ggrepel

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4 标签、标注、标度、主题等

ggplot(diamonds, aes(carat, price)) +
  geom_bin2d() + 
  scale_x_log10() +
  scale_y_log10()

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4 标签、标注、标度、主题等

ggplot(mpg, aes(displ, hwy)) +
  geom_point() +
  scale_y_continuous(
    name = "Highway fuel economy (mpg)",
    breaks = seq(0, 50, by = 10),
    limits = c(0, 50)
  )

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4 标签、标注、标度、主题等

ggplot(mpg, aes(displ, hwy)) +
  geom_point(aes(colour = drv, shape = drv)) +
  scale_colour_brewer(palette = "Set1")   # RColorBrewer::display.brewer.all()

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4 标签、标注、标度、主题等

ggplot(mpg, aes(displ, hwy, colour = class)) +
  geom_point() +
  theme(legend.position = "bottom") +
  guides(
    colour = guide_legend(nrow = 1, override.aes = list(size = 3))
  )

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4 标签、标注、标度、主题等

ggplot(mpg, aes(displ, hwy)) +
  geom_point(aes(colour = class)) +
  geom_smooth(se = FALSE) +
  theme_minimal()

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4 标签、标注、标度、主题等

ggplot(mpg, aes(displ, hwy)) +
  geom_point(aes(colour = class)) +
  geom_smooth(se = FALSE) +
  theme_minimal()

ggplot(mpg, aes(displ, hwy)) +
  geom_point(aes(colour = class)) +
  geom_smooth(se = FALSE) +
  ggthemes::theme_stata()   # install it!

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4 标签、标注、标度、主题等

theme(line, rect, text, title, aspect.ratio, axis.title, axis.title.x,
      axis.title.x.top, axis.title.x.bottom, axis.title.y, axis.title.y.left,
      axis.title.y.right, axis.text, axis.text.x, axis.text.x.top,
      axis.text.x.bottom, axis.text.y, axis.text.y.left, axis.text.y.right,
      axis.ticks, axis.ticks.x, axis.ticks.x.top, axis.ticks.x.bottom, axis.ticks.y,
      axis.ticks.y.left, axis.ticks.y.right, axis.ticks.length, axis.ticks.length.x,
      axis.ticks.length.x.top, axis.ticks.length.x.bottom, axis.ticks.length.y,
      axis.ticks.length.y.left, axis.ticks.length.y.right, axis.line, axis.line.x,
      axis.line.x.top, axis.line.x.bottom, axis.line.y, axis.line.y.left,
      axis.line.y.right, legend.background, legend.margin, legend.spacing,
      legend.spacing.x, legend.spacing.y, legend.key, legend.key.size,
      legend.key.height, legend.key.width, legend.text, legend.text.align,
      legend.title, legend.title.align, legend.position, legend.direction,
      legend.justification, legend.box, legend.box.just, legend.box.margin,
      legend.box.background, legend.box.spacing, panel.background, panel.border,
      panel.spacing, panel.spacing.x, panel.spacing.y, panel.grid, panel.grid.major,
      panel.grid.minor, panel.grid.major.x, panel.grid.major.y, panel.grid.minor.x,
      panel.grid.minor.y, panel.ontop, plot.background, plot.title,
      plot.title.position, plot.subtitle, plot.caption, plot.caption.position,
      plot.tag, plot.tag.position, plot.margin, strip.background, strip.background.x,
      strip.background.y, strip.clip, strip.placement, strip.text, strip.text.x,
      strip.text.x.bottom, strip.text.x.top, strip.text.y, strip.text.y.left,
      strip.text.y.right, strip.switch.pad.grid, strip.switch.pad.wrap, ...,
      complete = FALSE, validate = TRUE)
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