R语言可视化(七):箱线图绘制

07.箱线图绘制


清除当前环境中的变量

rm(list=ls())

设置工作目录

setwd("C:/Users/Dell/Desktop/R_Plots/07boxplot/")

基础boxplot函数绘制箱线图

## boxplot on a formula:
# 查看内置数据集
head(InsectSprays)
##   count spray
## 1    10     A
## 2     7     A
## 3    20     A
## 4    14     A
## 5    14     A
## 6    12     A

boxplot(count ~ spray, data = InsectSprays, col = "lightgray")
image.png
boxplot(count ~ spray, data = InsectSprays,
        notch = TRUE, col = "blue")
## Warning in bxp(list(stats = structure(c(7, 11, 14, 18.5, 23, 7, 12, 16.5, :
## some notches went outside hinges ('box'): maybe set notch=FALSE
image.png
## boxplot on a matrix:
mat <- cbind(Uni05 = (1:100)/21, Norm = rnorm(100),
             `5T` = rt(100, df = 5), Gam2 = rgamma(100, shape = 2))
head(mat)
##           Uni05       Norm          5T      Gam2
## [1,] 0.04761905  0.7106628  1.36924396 5.6044293
## [2,] 0.09523810  1.0806786  0.55538157 0.9160426
## [3,] 0.14285714  0.8803233 -1.14302098 3.7818738
## [4,] 0.19047619 -0.3892679  0.96060571 1.8471195
## [5,] 0.23809524  0.6940575 -0.03855087 1.2075029
## [6,] 0.28571429 -1.1620767  4.36417197 3.5148279

boxplot(mat) # directly, calling boxplot.matrix()
image.png
## boxplot on a data frame:
df <- as.data.frame(mat)
par(las = 1) # all axis labels horizontal
boxplot(df, main = "boxplot(*, horizontal = TRUE)", 
        col = "red", notch = T, horizontal = TRUE)
image.png
## Using 'at = ' and adding boxplots -- example idea by Roger Bivand :
head(ToothGrowth)
##    len supp dose
## 1  4.2   VC  0.5
## 2 11.5   VC  0.5
## 3  7.3   VC  0.5
## 4  5.8   VC  0.5
## 5  6.4   VC  0.5
## 6 10.0   VC  0.5

boxplot(len ~ dose, data = ToothGrowth,
        subset = supp == "VC", 
        at = 1:3 - 0.2,
        boxwex = 0.25, 
        col = "yellow",
        main = "Guinea Pigs' Tooth Growth",
        xlab = "Vitamin C dose mg",
        ylab = "tooth length",
        xlim = c(0.5, 3.5), ylim = c(0, 35), yaxs = "i")
boxplot(len ~ dose, data = ToothGrowth, 
        add = TRUE,
        subset = supp == "OJ", 
        at = 1:3 + 0.2,
        boxwex = 0.25,
        col = "orange")
legend("topleft", c("Ascorbic acid", "Orange juice"),
       fill = c("yellow", "orange"))
image.png
## With less effort (slightly different) using factor *interaction*:
boxplot(len ~ dose:supp, data = ToothGrowth,
        boxwex = 0.5, col = c("orange", "yellow"),
        main = "Guinea Pigs' Tooth Growth",
        xlab = "Vitamin C dose mg", ylab = "tooth length",
        sep = ":", lex.order = TRUE, ylim = c(0, 35), yaxs = "i")
image.png

ggplot2包绘制箱线图

library(ggplot2)

data <- read.table("demo1_boxplot.txt",header = T)
head(data)
##   BRCA1 sample_type
## 1  4.53       Tumor
## 2  6.28       Tumor
## 3  6.38       Tumor
## 4  6.45       Tumor
## 5  6.67       Tumor
## 6  6.84       Tumor

ggplot(data,aes(sample_type,BRCA1,fill=sample_type)) + 
        geom_boxplot()
image.png
# 添加扰动点,更改离群点的颜色,形状和大小
ggplot(data,aes(sample_type,BRCA1,fill=sample_type)) + 
        geom_boxplot(width=0.5,outlier.color = "red",outlier.shape = 2,outlier.size = 3) + 
        geom_jitter(shape=16, position=position_jitter(0.2))
image.png
# 添加notch,更改颜色
ggplot(data,aes(sample_type,BRCA1,fill=sample_type)) + 
        geom_boxplot(notch = T,width=0.5,alpha=0.8) + 
        scale_fill_brewer(palette="Set1")
image.png
# 添加均值点
ggplot(data,aes(sample_type,BRCA1,fill=sample_type)) + 
        geom_boxplot(notch = T,width=0.5,alpha=0.8) + 
        scale_fill_brewer(palette="Set1") + 
        stat_summary(fun.y="mean",geom="point",shape=23,
                     size=4,fill="white")
image.png
# 添加误差棒
ggplot(data,aes(sample_type,BRCA1,fill=sample_type)) + 
        geom_boxplot(notch = T,width=0.5,alpha=0.8) + 
        stat_boxplot(geom = "errorbar",width=0.1) +
        scale_fill_brewer(palette="Set1") + 
        stat_summary(fun.y="mean",geom="point",shape=23,
                     size=4,fill="white")
image.png
# 更换主题背景,旋转坐标轴
ggplot(data,aes(sample_type,BRCA1,fill=sample_type)) + 
        stat_boxplot(geom = "errorbar",width=0.1) +
        geom_boxplot(notch = T,width=0.5,alpha=0.8) + 
        scale_fill_brewer(palette="Set1") + 
        stat_summary(fun.y="mean",geom="point",
                     shape=23,size=4,fill="white") +
        theme_bw() + coord_flip()

image.png

ggpubr包绘制箱线图

library(ggpubr)

data <- read.table("demo1_boxplot.txt",header = T)
head(data)
##   BRCA1 sample_type
## 1  4.53       Tumor
## 2  6.28       Tumor
## 3  6.38       Tumor
## 4  6.45       Tumor
## 5  6.67       Tumor
## 6  6.84       Tumor

ggboxplot(data,x="sample_type",y="BRCA1",
          width = 0.6,fill="sample_type")
image.png
# 添加notch,扰动点,更改颜色
ggboxplot(data,x="sample_type",y="BRCA1",
          width = 0.6,fill="sample_type",
          notch = T,palette = c("#00AFBB", "#E7B800"),
          add = "jitter",shape="sample_type")
image.png
# 添加误差棒和均值
ggboxplot(data,x="sample_type",y="BRCA1",
          width = 0.6,fill="sample_type",
          bxp.errorbar = T, bxp.errorbar.width = 0.2,
          add = "mean",add.params = list(size=1,color="white"))
image.png
# 旋转坐标轴
ggboxplot(data,x="sample_type",y="BRCA1",
          width = 0.6,fill="sample_type",
          add = "mean",add.params = list(size=1,color="white"),
          notch = T,orientation = "horizontal")
image.png
sessionInfo()
## R version 3.6.0 (2019-04-26)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 18363)
## 
## Matrix products: default
## 
## locale:
## [1] LC_COLLATE=Chinese (Simplified)_China.936 
## [2] LC_CTYPE=Chinese (Simplified)_China.936   
## [3] LC_MONETARY=Chinese (Simplified)_China.936
## [4] LC_NUMERIC=C                              
## [5] LC_TIME=Chinese (Simplified)_China.936    
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] ggpubr_0.2.1  magrittr_1.5  ggplot2_3.2.0
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.1         knitr_1.23         tidyselect_0.2.5  
##  [4] munsell_0.5.0      colorspace_1.4-1   R6_2.4.0          
##  [7] rlang_0.4.0        stringr_1.4.0      dplyr_0.8.3       
## [10] tools_3.6.0        grid_3.6.0         gtable_0.3.0      
## [13] xfun_0.8           withr_2.1.2        htmltools_0.3.6   
## [16] yaml_2.2.0         lazyeval_0.2.2     digest_0.6.20     
## [19] assertthat_0.2.1   tibble_2.1.3       ggsignif_0.5.0    
## [22] crayon_1.3.4       RColorBrewer_1.1-2 purrr_0.3.2       
## [25] glue_1.3.1         evaluate_0.14      rmarkdown_1.13    
## [28] labeling_0.3       stringi_1.4.3      compiler_3.6.0    
## [31] pillar_1.4.2       scales_1.0.0       pkgconfig_2.0.2