R语言利用ggplot2绘制QQ图和箱线图详解-开发语言

这篇文章主要为大家介绍了R语言如何利用ggplot2绘制QQ图和箱线图，文中的示例代码讲解详细，对我们学习R语言有一定的帮助，需要的可以参考一下

绘制qq图

在ggplot2中绘制qq图需要两步，geom_qq()将绘制样本分位点，geom_qq_line()将绘制标准正态线

函数介绍

geom_qq()

geom_qq(
  mapping = NULL,
  data = NULL,
  geom = "point",
  position = "identity",
  ...,
  distribution = stats::qnorm,
  dparams = list(),
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_qq_line(
  mapping = NULL,
  data = NULL,
  geom = "path",
  position = "identity",
  ...,
  distribution = stats::qnorm,
  dparams = list(),
  line.p = c(0.25, 0.75),
  fullrange = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

参数介绍

**aes()**中的映射参数必须包含sample，可选参数有group,x,y distribution

Distribution function to use, if x not specified
dparams Additional parameters passed on to distribution function.
line.p Vector of quantiles to use when fitting the Q-Q line, defaults defaults to c(.25, .75).
fullrange Should the q-q line span the full range of the plot, or just the data

注意事项

**aes()**中的映射参数必须包含sample

例子

Using to explore the distribution of a variable

ggplot(mtcars, aes(sample = mpg)) +
  stat_qq() +
  stat_qq_line()
ggplot(mtcars, aes(sample = mpg, colour = factor(cyl))) +
  stat_qq() +
  stat_qq_line()

绘制boxplot

函数介绍

geom_boxplot(
  mapping = NULL,
  data = NULL,
  stat = "boxplot",
  position = "dodge2",
  ...,
  outlier.colour = NULL,
  outlier.color = NULL,
  outlier.fill = NULL,
  outlier.shape = 19,
  outlier.size = 1.5,
  outlier.stroke = 0.5,
  outlier.alpha = NULL,
  notch = FALSE,
  notchwidth = 0.5,
  varwidth = FALSE,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

参数介绍

aes()可接收的参数有：

x or y，利用x将会是横向箱线图，y的是纵向
lower or xlower
upper or xupper
middle or xmiddle
ymin or xmin
ymax or xmax
alpha
colour
fill
group
linetype
shape
size
weight

notch If FALSE (default) make a standard box plot. If TRUE, make a notched box plot. Notches are used to compare groups; if the notches
of two boxes do not overlap, this suggests that the medians are
significantly different.
notchwidth For a notched box plot, width of the notch relative to the body (defaults to notchwidth = 0.5).
varwidth If FALSE (default) make a standard box plot. If TRUE, boxes are drawn with widths proportional to the square-roots of the
number of observations in the groups (possibly weighted, using the
weight aesthetic).

例子

p <- ggplot(mpg, aes(x=class, y=hwy))
p + geom_boxplot()

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

p <- ggplot(mpg, aes(x=class, y=hwy))
p + geom_boxplot(notch = TRUE,varwidth = TRUE,fill = "white", colour = "#3366FF")

ggplot(diamonds, aes(carat, price)) +
  geom_boxplot(aes(group = cut_width(carat, 0.25)))

p <- ggplot(mpg, aes(x=class, y=hwy))
p + geom_boxplot(outlier.shape = NA) + geom_jitter(width = 0.2)

利用分位点绘制箱线图

y <- rnorm(100)
df <- data.frame(
  x = 1,
  y0 = min(y),
  y25 = quantile(y, 0.25),
  y50 = median(y),
  y75 = quantile(y, 0.75),
  y100 = max(y)
)
ggplot(df, aes(x)) +
  geom_boxplot(
    aes(ymin = y0, lower = y25, middle = y50, upper = y75, ymax = y100),
    stat = "identity"
  )

将QQ图和箱线图进行融合

函数介绍

该函数是来自于qqboxplot包，因此使用前需要安装

geom_qqboxplot(
  mapping = NULL,
  data = NULL,
  stat = "qqboxplot",
  position = "dodge2",
  ...,
  outlier.colour = NULL,
  outlier.color = NULL,
  outlier.fill = NULL,
  outlier.shape = 19,
  outlier.size = 1.5,
  outlier.stroke = 0.5,
  outlier.alpha = NULL,
  notch = FALSE,
  notchwidth = 0.5,
  varwidth = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

参数介绍

大部分参数和geom_qq()和geom_boxplot()中的参数含义相同

reference_dist 表示参数比较的标准分布名称，如果有参数需要有dparams

compdata 用于比较的标准样本数据，是个向量

注意事项

aes()函数中的y不可缺

例子

library(dplyr)
library(ggplot2)
library(qqboxplot)

simulated_data=tibble(y=c(rnorm(1000, mean=2), rt(1000, 16), rt(500, 4), 
                          rt(1000, 8), rt(1000, 32)),
                      group=c(rep("normal, mean=2", 1000), 
                              rep("t distribution, df=16", 1000), 
                              rep("t distribution, df=4", 500), 
                              rep("t distribution, df=8", 1000), 
                              rep("t distribution, df=32", 1000)))
p <- ggplot2::ggplot(simulated_data, ggplot2::aes(factor(group,
                                                         levels=c("normal, mean=2", "t distribution, df=32", "t distribution, df=16",
                                                                  "t distribution, df=8", "t distribution, df=4")), y=y))
p + geom_qqboxplot()
p + geom_qqboxplot(reference_dist = "norm")


p + geom_qqboxplot(compdata = comparison_dataset)