Hadley Wickham创建的可视化包ggplot2可以流畅地进行优美的可视化，但是如果要通过ggplot2定制一套图形，尤其是适用于杂志期刊等出版物的图形，对于那些没有深入了解ggplot2的人来说就有点困难了，ggplot2的部分语法是很晦涩的。为此Alboukadel Kassambara创建了基于ggplot2的可视化包ggpubr用于绘制符合出版物要求的图形。
安装及加载ggpubr包
安装方式有两种：
- 直接从CRAN安装：
install.packages("ggpubr")
- 从GitHub上安装最新版本：
if(!require(devtools)) install.packages("devtools")
devtools::install_github("kassambara/ggpubr")
安装完之后直接加载就行：
library(ggpubr)
ggpubr可绘制图形：
ggpubr可绘制大部分我们常用的图形，下面一一介绍。
分布图(Distribution)
#构建数据集
set.seed(1234)
df <- data.frame( sex=factor(rep(c("f", "M"), each=200)),
weight=c(rnorm(200, 55), rnorm(200, 58)))
head(df)
## sex weight
## 1 f 53.79293
## 2 f 55.27743
## 3 f 56.08444
## 4 f 52.65430
## 5 f 55.42912
## 6 f 55.50606
密度分布图以及边际地毯线并添加平均值线
ggdensity(df, x="weight", add = "mean", rug = TRUE, color = "sex", fill = "sex",
palette = c("#00AFBB", "#E7B800"))
带有均值线和边际地毯线的直方图
gghistogram(df, x="weight", add = "mean", rug = TRUE, color = "sex", fill = "sex",
palette = c("#00AFBB", "#E7B800"))
箱线图与小提琴图
#加载数据集ToothGrowth
data("ToothGrowth")
df1 <- ToothGrowth
head(df1)
## 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
p <- ggboxplot(df1, x="dose", y="len", color = "dose",
palette = c("#00AFBB", "#E7B800", "#FC4E07"),
add = "jitter", shape="dose")#增加了jitter点，点shape由dose映射p
增加不同组间的p-value值，可以自定义需要标注的组间比较
my_comparisons <- list(c("0.5", "1"), c("1", "2"), c("0.5", "2"))
p+stat_compare_means(comparisons = my_comparisons)+#不同组间的比较
stat_compare_means(label.y = 50)
内有箱线图的小提琴图
ggviolin(df1, x="dose", y="len", fill = "dose",
palette = c("#00AFBB", "#E7B800", "#FC4E07"),
add = "boxplot", add.params = list(fill="white"))+
stat_compare_means(comparisons = my_comparisons, label = "p.signif")+#label这里表示选择显著性标记（星号）
stat_compare_means(label.y = 50)
条形图
data("mtcars")
df2 <- mtcars
df2$cyl <- factor(df2$cyl)
df2$name <- rownames(df2)#添加一行name
head(df2[, c("name", "wt", "mpg", "cyl")])
按从小到大顺序绘制条形图（不分组排序）
ggbarplot(df2, x="name", y="mpg", fill = "cyl", color = "white",
palette = "jco",#杂志jco的配色
sort.val = "desc",#下降排序
sort.by.groups=FALSE,#不按组排序
x.text.angle=60)
按组进行排序
ggbarplot(df2, x="name", y="mpg", fill = "cyl", color = "white",
palette = "jco",#杂志jco的配色
sort.val = "asc",#上升排序,区别于desc，具体看图演示
sort.by.groups=TRUE,#按组排序
x.text.angle=90)
偏差图
偏差图展示了与参考值之间的偏差
df2$mpg_z <- (df2$mpg-mean(df2$mpg))/sd(df2$mpg)
df2$mpg_grp <- factor(ifelse(df2$mpg_z<0, "low", "high"), levels = c("low", "high"))
head(df2[, c("name", "wt", "mpg", "mpg_grp", "cyl")])
绘制排序过的条形图
ggbarplot(df2, x="name", y="mpg_z", fill = "mpg_grp", color = "white",
palette = "jco", sort.val = "asc", sort.by.groups = FALSE, x.text.angle=60,
ylab = "MPG z-score", xlab = FALSE, legend.title="MPG Group")
坐标轴变换
ggbarplot(df2, x="name", y="mpg_z", fill = "mpg_grp", color = "white",
palette = "jco", sort.val = "desc", sort.by.groups = FALSE,
x.text.angle=90, ylab = "MPG z-score", xlab = FALSE,
legend.title="MPG Group", rotate=TRUE, ggtheme = theme_minimal())
点图(Dot charts)
棒棒糖图(Lollipop chart)
棒棒图可以代替条形图展示数据
ggdotchart(df2, x="name", y="mpg", color = "cyl",
palette = c("#00AFBB", "#E7B800", "#FC4E07"), sorting = "ascending",
add = "segments", ggtheme = theme_pubr())
可以自设置各种参数
ggdotchart(df2, x="name", y="mpg", color = "cyl",
palette = c("#00AFBB", "#E7B800", "#FC4E07"), sorting = "descending",
add = "segments", rotate = TRUE, group = "cyl", dot.size = 6,
label = round(df2$mpg), font.label = list(color="white", size=9, vjust=0.5),
ggtheme = theme_pubr())
偏差图
ggdotchart(df2, x="name", y="mpg_z", color = "cyl",
palette = c("#00AFBB", "#E7B800", "#FC4E07"), sorting = "descending",
add = "segment", add.params = list(color="lightgray", size=2),
group = "cyl", dot.size = 6, label = round(df2$mpg_z, 1),
font.label = list(color="white", size=9, vjust=0.5), ggtheme = theme_pubr())+
geom_line(yintercept=0, linetype=2, color="lightgray")
Cleveland点图
ggdotchart(df2, x="name", y="mpg", color = "cyl",
palette = c("#00AFBB", "#E7B800", "#FC4E07"), sorting = "descending",
rotate = TRUE, dot.size = 2, y.text.col=TRUE, ggtheme = theme_pubr())+
theme_cleveland()
SessionInfo
sessionInfo()
## R version 3.4.0 (2017-04-21)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 8.1 x64 (build 9600)
##
## 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_0.1.3 magrittr_1.5 ggplot2_2.2.1
##
## loaded via a namespace (and not attached):
## [1] Rcpp_0.12.11 knitr_1.16 munsell_0.4.3 colorspace_1.3-2
## [5] R6_2.2.1 rlang_0.1.1 stringr_1.2.0 plyr_1.8.4
## [9] dplyr_0.5.0 tools_3.4.0 grid_3.4.0 gtable_0.2.0
## [13] DBI_0.6-1 htmltools_0.3.6 yaml_2.1.14 lazyeval_0.2.0
## [17] rprojroot_1.2 digest_0.6.12 assertthat_0.2.0 tibble_1.3.3
## [21] ggsignif_0.2.0 ggsci_2.4 purrr_0.2.2.2 evaluate_0.10
## [25] rmarkdown_1.5 labeling_0.3 stringi_1.1.5 compiler_3.4.0
## [29] scales_0.4.1 backports_1.1.0
