作者简介Introduction

taoyan：伪码农，R语言爱好者，爱开源。

个人博客: https://ytlogos.github.io/

往期回顾

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library(ggplot2)

#使用数据集mtcars演示

ggplot(mtcars)+ geom_point(aes(wt, mpg), color="red")+geom_text(aes(wt, mpg, label=rownames(mtcars)))+theme_classic(base_size = 16)

library(ggrepel)

set.seed(42)

ggplot(mtcars)+ geom_point(aes(wt, mpg), color="red")+

geom_text_repel(aes(wt, mpg, label=rownames(mtcars)))+

theme_classic(base_size = 16)

set.seed(42)

ggplot(mtcars)+ geom_point(aes(wt, mpg), color="grey", size=5)+

geom_label_repel(aes(wt, mpg, fill=factor(cyl),

label=rownames(mtcars)), fontface="bold", color="white",

box.padding=unit(0.35, "lines"), point.padding=unit(0.5, "lines"),

segment.colour = "grey50")+ theme_classic(base_size = 16)

set.seed(42)

ggplot(mtcars)+ geom_point(aes(wt, mpg, color=factor(cyl)), size=3)+

geom_text_repel(aes(wt, mpg, color=factor(cyl),

label=rownames(mtcars), angle=ifelse(mtcars$cyl==4, 90, 0)),

size=4, family="Times", fontface="bold",

box.padding=unit(0.5, "lines"), point.padding=unit(1.6, "lines"),

segment.color = "#cccccc", segment.size = 0.5,

arrow = arrow(length=unit(0.01, "npc")),force = 1, max.iter = 3e3,

nudge_x = ifelse(mtcars$cyl==6, 2, 0), nudge_y = ifelse(mtcars$cyl==6, 9, 0))+

scale_color_discrete(name="cyl")+

scale_x_continuous(expand = c(0.5, 0))+

scale_y_continuous(expand = c(0.25, 0))+

theme_classic(base_size = 16)

set.seed(42)

mtcars$label <- rownames(mtcars)

ggplot(mtcars, aes(wt, mpg, label=label))+

geom_point(color="red")+ geom_text_repel(point.padding = NA)+

theme_classic(base_size = 16)

set.seed(42)

mtcars$label <- rownames(mtcars)

mtcars$label[1:15] <- ""

ggplot(mtcars, aes(wt, mpg))+ geom_point(aes(color=factor(cyl)), size=2)+

geom_text_repel(aes(color=factor(cyl), size=hp, label=label),

point.padding = unit(0.25, "lines"), box.padding = unit(0.25, "lines"),

nudge_y = 0.1)+ theme_classic(base_size = 16)

set.seed(42)

data <- mtcars

mu <- mean(data$wt)

left <- data[data$wt <mu, ]

right <- data[data$wt>=mu, ]

ggplot()+ geom_vline(xintercept = mu)+

geom_point(aes(wt, mpg), data=data)+

geom_text_repel(data=left, aes(wt, mpg, label=rownames(left),

color="Left half"), xlim=c(NA, mu))+

geom_text_repel(data=right, aes(wt, mpg, label=rownames(right),

color="Rigth half"), xlim=c(mu, NA))+ theme_classic(base_size = 16)

set.seed(42)

#direction="x" 左右移动

ggplot(mtcars)+

geom_point(aes(wt, mpg), color="red")+

geom_text_repel(aes(wt, mpg, label=rownames(mtcars)), direction="x")+

theme_classic(base_size = 16)+xlim(1, 6)

#direction="x" 上下移动

ggplot(mtcars)+

geom_point(aes(wt, mpg), color="red")+

geom_text_repel(aes(wt, mpg, label=rownames(mtcars)), direction="y")+

theme_classic(base_size = 16)+xlim(1, 6)

set.seed(42)

ggplot(Orange, aes(age, circumference, color=Tree))+

geom_line()+

coord_cartesian(xlim=c(min(Orange$age), max(Orange$age)+90))+

geom_text_repel(data=subset(Orange, age==max(age)),

aes(label=paste("Tree", Tree)),size=6, nudge_x = 45, segment.color = NA)+

theme_classic(base_size = 16)+

theme(legend.position = "none")+

labs(title="Orange Trees", x="Age(days)", y="Circumference(mm)")

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] ggrepel_0.6.5 ggplot2_2.2.1

##

## loaded via a namespace (and not attached):

## [1] Rcpp_0.12.11 digest_0.6.12 rprojroot_1.2 plyr_1.8.4

## [5] grid_3.4.0 gtable_0.2.0 backports_1.1.0 magrittr_1.5

## [9] evaluate_0.10 scales_0.4.1 rlang_0.1.1 stringi_1.1.5

## [13] lazyeval_0.2.0 rmarkdown_1.5 labeling_0.3 tools_3.4.0

## [17] stringr_1.2.0 munsell_0.4.3 yaml_2.1.14 compiler_3.4.0

## [21] colorspace_1.3-2 htmltools_0.3.6 knitr_1.16 tibble_1.3.3