r语言descstats_一条命令轻松绘制CNS顶级配图-ggpubr
Hadley Wickham創(chuàng)建的可視化包ggplot2可以流暢地進(jìn)行優(yōu)美的可視化,但是如果要通過ggplot2定制一套圖形,尤其是適用于雜志期刊等出版物的圖形,對(duì)于那些沒有深入了解ggplot2的人來說就有點(diǎn)困難了,ggplot2的部分語法是很晦澀的。為此Alboukadel Kassambara創(chuàng)建了基于ggplot2的可視化包ggpubr用于繪制符合出版物要求的圖形。
安裝及加載ggpubr包
# 直接從CRAN安裝
install.packages("ggpubr", repo="http://cran.us.r-project.org")
# 從GitHub上安裝最新版本
install.packages("devtools", repo="http://cran.us.r-project.org")
library(devtools)
install_github("kassambara/ggpubr")
# 安裝完之后直接加載就行:
library(ggpubr)
ggpubr可繪制圖形
ggpubr可繪制大部分我們常用的圖形,下面逐個(gè)介紹。
分布圖(Distribution)
帶有均值線和地毯線的密度圖
#構(gòu)建數(shù)據(jù)集
set.seed(123)
df
weight=c(rnorm(200, 55), rnorm(200, 58)))
# 預(yù)覽數(shù)據(jù)格式
head(df)
# 繪制密度圖
ggdensity(df, x="weight", add = "mean", rug = TRUE, color = "sex", fill = "sex",
palette = c("#00AFBB", "#E7B800"))
圖1. 密度圖展示不同性別分組下體重的分布,X軸為體重,Y軸為自動(dòng)累計(jì)的密度,X軸上添加地毯線進(jìn)一步呈現(xiàn)樣本的分布;按性別分別組標(biāo)記輪廓線顏色,再按性別填充色展示各組的分布,使用palette自定義顏色,是不是很舒服。
帶有均值線和邊際地毯線的直方圖
gghistogram(df, x="weight", add = "mean", rug = TRUE, color = "sex", fill = "sex",
palette = c("#00AFBB", "#E7B800"))
圖2. 帶有均值線和邊際地毯線的直方圖,只是把密度比例還原為了原始數(shù)據(jù)counts值
箱線/小提琴圖(barplot/violinplot)
箱線圖+分組形狀+統(tǒng)計(jì)
#加載數(shù)據(jù)集ToothGrowth
data("ToothGrowth")
df1
head(df1)
p
palette = c("#00AFBB", "#E7B800", "#FC4E07"),
add = "jitter", shape="dose")#增加了jitter點(diǎn),點(diǎn)shape由dose映射
p
圖3. 箱線圖按組著色,同時(shí)樣本點(diǎn)標(biāo)記不同形狀可以一步區(qū)分組或批次
箱線圖+分組形狀+統(tǒng)計(jì)
# 增加不同組間的p-value值,可以自定義需要標(biāo)注的組間比較
my_comparisons
p+stat_compare_means(comparisons = my_comparisons)+ #不同組間的比較
stat_compare_means(label.y = 50)
圖4. stat_compare_means添加組間比較連線和統(tǒng)計(jì)P值
內(nèi)有箱線圖的小提琴圖+星標(biāo)記
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這里表示選擇顯著性標(biāo)記(星號(hào)) stat_compare_means(label.y = 50)
圖5. ggviolin繪制小提琴圖, add = "boxplot"中間再添加箱線圖,stat_compare_means中,設(shè)置lable="p.signif",即可添加星添加組間比較連線和統(tǒng)計(jì)P值按星分類。
條形/柱狀圖(barplot)
data("mtcars")
df2
df2$cyl
df2$name
head(df2[, c("name", "wt", "mpg", "cyl")])
ggbarplot(df2, x="name", y="mpg", fill = "cyl", color = "white",
palette = "npg", #雜志nature的配色
sort.val = "desc", #下降排序
sort.by.groups=FALSE, #不按組排序
x.text.angle=60)
圖6. 柱狀圖展示不同車的速度,按cyl為分組信息進(jìn)行填充顏色,顏色按nature配色方法(支持 ggsci包中的本色方案,如: "npg", "aaas", "lancet", "jco", "ucscgb", "uchicago", "simpsons" and "rickandmorty"),按數(shù)值降序排列。
# 按組進(jìn)行排序
ggbarplot(df2, x="name", y="mpg", fill = "cyl", color = "white",
palette = "aaas", #雜志Science的配色
sort.val = "asc", #上升排序,區(qū)別于desc,具體看圖演示
sort.by.groups=TRUE,x.text.angle=60) #按組排序 x.text.angle=90
圖7. 由上圖中顏色改為Sciences配色方案(為什么感覺nature和sciences的配色方案沒有文章里的看著舒服呢?),按組升序排布,且調(diào)整x軸標(biāo)簽60度角防止重疊。
偏差圖
偏差圖展示了與參考值之間的偏差
df2$mpg_z
df2$mpg_grp
head(df2[, c("name", "wt", "mpg", "mpg_grp", "cyl")])
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")
圖8. 基于Zscore的柱狀圖,就是原始值減均值,再除標(biāo)準(zhǔn)差。按jco雜志配色方案,升序排列,不按組排列。
坐標(biāo)軸變換
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()) # rotate設(shè)置x/y軸對(duì)換
圖9. rotate=TRUE翻轉(zhuǎn)坐標(biāo)軸,柱狀圖秒變條形圖
棒棒糖圖(Lollipop chart)
棒棒圖可以代替條形圖展示數(shù)據(jù)
ggdotchart(df2, x="name", y="mpg", color = "cyl",
palette = c("#00AFBB", "#E7B800", "#FC4E07"),
sorting = "ascending",
add = "segments", ggtheme = theme_pubr())
圖10. 柱狀圖太多了單調(diào),改用棒棒糖圖添加多樣性
可以自設(shè)置各種參數(shù)
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$mpg), font.label = list(color="white",
size=9, vjust=0.5), ggtheme = theme_pubr())
圖11. 棒棒糖圖簡(jiǎn)單調(diào)整,rotate = TRUE轉(zhuǎn)換坐標(biāo)軸, dot.size = 6調(diào)整糖的大小,label = round()添加糖心中的數(shù)值,font.label進(jìn)一步設(shè)置字體樣式
棒棒糖偏差圖
ggdotchart(df2, x="name", y="mpg_z", color = "cyl",
palette = c("#00AFBB", "#E7B800", "#FC4E07"),
sorting = "descending", add = "segment",
add.params = list(color="lightgray", size=2),
group= "cyl", dot.size = 6, label = round(df2$mpg_z, 1),
font.label = list(color="white", size=9, vjust=0.5),
ggtheme = theme_pubr())+ geom_line(yintercept=0, linetype=2, color="lightgray")
圖12. 同柱狀圖類似,用Z-score的值代替原始值繪圖。
Cleveland點(diǎn)圖
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()
圖13. theme_cleveland()主題可設(shè)置為Cleveland點(diǎn)圖樣式
我測(cè)試的工作環(huán)境
sessionInfo()
R version 3.4.1 (2017-06-30)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.3 LTS
Matrix products: default
BLAS: /usr/lib/openblas-base/libblas.so.3
LAPACK: /usr/lib/libopenblasp-r0.2.18.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] bindrcpp_0.2 ggpubr_0.1.6.999 magrittr_1.5 ggplot2_2.2.1 devtools_1.13.4
loaded via a namespace (and not attached):
[1] Rcpp_0.12.14 bindr_0.1 munsell_0.4.3 colorspace_1.3-2 R6_2.2.2 rlang_0.1.4 httr_1.3.1
[8] plyr_1.8.4 dplyr_0.7.4 tools_3.4.1 grid_3.4.1 gtable_0.2.0 git2r_0.19.0 withr_2.1.0
[15] lazyeval_0.2.1 digest_0.6.12 assertthat_0.2.0 tibble_1.3.4 ggsignif_0.4.0 ggsci_2.8 purrr_0.2.4
[22] curl_3.0 memoise_1.1.0 glue_1.2.0 labeling_0.3 compiler_3.4.1 scales_0.5.0 pkgconfig_2.0.1
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