学习tidyverse - 数据可视化(1)

Prerequisites

install.packages("tidyverse")
library(tidyverse)

我们使用ggplot2中的mpg数据框进行分析测试。 mpg包含美国环境保护署收集的有关38辆汽车的观察结果。

mpg
#> # A tibble: 234 x 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     compa…
#> 2 audi         a4      1.8  1999     4 manual(m5) f        21    29 p     compa…
#> 3 audi         a4      2    2008     4 manual(m6) f        20    31 p     compa…
#> 4 audi         a4      2    2008     4 auto(av)   f        21    30 p     compa…
#> 5 audi         a4      2.8  1999     6 auto(l5)   f        16    26 p     compa…
#> 6 audi         a4      2.8  1999     6 manual(m5) f        18    26 p     compa…
#> # … with 228 more rows

displ: 表示汽车引擎大小（以升为单位）。
hwy: 高速公路上的汽车燃油效率，以英里/加仑（mpg）为单位。 当相同距离行驶时，低燃油效率的汽车比高燃油效率的汽车消耗更多的燃油。

1. Statistical transformations

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

通常，可以互换使用geoms和stats。 例如，可以使用stat_count（）而不是geom_bar（）重新创建上一个图：

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

在下面的代码中，将geom_bar（）的统计信息从count（默认值）更改为identity。

demo <- tribble(
  ~cut,         ~freq,
  "Fair",       1610,
  "Good",       4906,
  "Very Good",  12082,
  "Premium",    13791,
  "Ideal",      21551
)

ggplot(data = demo) +
  geom_bar(mapping = aes(x = cut, y = freq), stat = "identity")

显示比例条形图，而不是计数条形图：

ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut, y = stat(prop), group = 1))

可以使用stat_summary（）来汇总每个唯一x值的y值：

ggplot(data = diamonds) + 
  stat_summary(
    mapping = aes(x = cut, y = depth),
    fun.min = min,
    fun.max = max,
    fun = median
  )

2. Position adjustments

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

如果将填充映射到另一个变量（如清晰度），条形图会自动堆叠。 每个彩色矩形代表切割和清晰度的组合。

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

position ="identity"将把每个对象从纵坐标底部排列。要看到重叠，需要通过设置alpha来使条形稍微透明，或者通过设置fill = NA来使条形完全透明。

ggplot(data = diamonds, mapping = aes(x = cut, fill = clarity)) + 
  geom_bar(alpha = 1/5, position = "identity")
ggplot(data = diamonds, mapping = aes(x = cut, colour = clarity)) + 
  geom_bar(fill = NA, position = "identity")

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

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

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy), position = "jitter")

3. Coordinate systems

coord_flip()切换x和y轴。

ggplot(data = mpg, mapping = aes(x = class, y = hwy)) + 
  geom_boxplot()
ggplot(data = mpg, mapping = aes(x = class, y = hwy)) + 
  geom_boxplot() +
  coord_flip()

nz <- map_data("nz")

ggplot(nz, aes(long, lat, group = group)) +
  geom_polygon(fill = "white", colour = "black")

ggplot(nz, aes(long, lat, group = group)) +
  geom_polygon(fill = "white", colour = "black") +
  coord_quickmap()

bar <- ggplot(data = diamonds) + 
  geom_bar(
    mapping = aes(x = cut, fill = cut), 
    show.legend = FALSE,
    width = 1
  ) + 
  theme(aspect.ratio = 1) +
  labs(x = NULL, y = NULL)

bar + coord_flip()
bar + coord_polar()