2  Histogram

非常简单的数据可视化形式,可以用base R::hist()或ggplot2::geom_histogram()来实现。

2.1 ggplot2

2.1.1 基本

library(tidyverse)

data = data.frame(value = rnorm(1000))

ggplot(data, aes(x = value)) +
  geom_histogram()

最基本的geom_histogram

library(hrbrthemes)

ggplot(data, aes(x=value)) + 
  geom_histogram(binwidth=0.1, fill="#69b3a2", color="#e9ecef", alpha=0.9) +
  theme_ipsum()

定制的geom_histogram

2.1.2 分组/镜像

还有用于比较两个变量分布(从0开始)的镜像直方图。

直方图的默认y = -..count..，因此可以通过设置y = -..count..来实现镜像效果。

data <- data.frame(
  var1 = rnorm(100),
  var2 = rnorm(100, mean = 2)
)

ggplot(data, aes(x = x)) +
  # 上方图
  geom_histogram(aes(x = var1, y = ..count..), fill = "#69b3a2") +
  geom_label(aes(x = 4.5, y = 6, label = "variable1"), color = "#69b3a2") +
  # 下方图,主要是通过y = -..count..来实现镜像
  geom_histogram(aes(x = var2, y = -..count..), fill = "#404080") +
  geom_label(aes(x = 4.5, y = -4, label = "variable2"), color = "#404080") 

通过y = -..count.. 来绘制镜像直方图

密度曲线图默认y = ..density..，因此可以通过设置y = -..density..来实现镜像效果。

下图,左侧是直方图(y改为密度),右侧是密度曲线图。

library(patchwork)

p1 <- ggplot(data, aes(x = x)) +
  # 上方图
  geom_histogram(aes(x = var1, y = ..density..), fill = "#69b3a2") +
  geom_label(aes(x = 3.5, y = 0.2, label = "variable1"), color = "#69b3a2") +
  # 下方图
  geom_histogram(aes(x = var2, y = -..density..), fill = "#404080") +
  geom_label(aes(x = 3.5, y = -0.2, label = "variable2"), color = "#404080") 

p2 <- ggplot(data, aes(x = x)) +
  # 上方图
  geom_density(aes(x = var1, y = ..density..), fill = "#69b3a2") +
  geom_label(aes(x = 3.5, y = 0.2, label = "variable1"), color = "#69b3a2") +
  # 下方图
  geom_density(aes(x = var2, y = -..density..), fill = "#404080") +
  geom_label(aes(x = 3.5, y = -0.2, label = "variable2"), color = "#404080")

p1 + p2

通过y = -..count.. 来绘制镜像直方图

data <- data.frame(
  type = c(rep("variable 1", 1000), rep("variable 2", 1000)),
  value = c(rnorm(1000), rnorm(1000, mean = 4))
)

ggplot(data, aes(x = value, fill = type)) +
  geom_histogram(color = "#e9ecef", alpha = 0.6, position = 'identity') +
  scale_fill_manual(values = c("#69b3a2", "#404080")) # 使用自定义颜色

通过fill来绘制双色直方图

2.1.3 分面

ggplot(iris, aes(x = `Sepal.Length`, fill = `Sepal.Length`)) + 
  geom_histogram() + 
  facet_wrap(~ Species, scale = "free_x")

facet_wrap分面,scale来控制自由坐标轴

2.1.4 边缘图

见 Section 3.3.9。

2.2 base R

查看 r-graph-gallery的例子。