ggplot2绘制高端散点图
2021-01-12 本文已影响0人
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绘制箭头的基础语法
geom_segment()在点(x,y)和(xend,yend)之间绘制一条直线
geom_curve画一条曲线
直线箭头
library(tidyverse)
ggplot(mtcars, aes(wt, mpg))+
geom_point()+
geom_segment(aes(x = 5,y = 30,xend = 3.5,yend = 25),
arrow = arrow(length = unit(0.4,"cm")))
曲线箭头
df <- data.frame(x1 = 2.62, x2 = 3.57, y1 = 21.0, y2 = 15.0)
ggplot(mtcars, aes(wt, mpg)) +
geom_point() + geom_curve(
aes(x = x1, y = y1, xend = x2, yend = y2),
data = df,size=1,color="red",angle = 90,
arrow = arrow(length = unit(0.03, "npc"),type="closed"))
改变箭头方向
ggplot(mtcars,aes(wt, mpg)) +
geom_point()+
geom_curve(aes(x = x1, y = y1, xend = x2, yend = y2),
data = df,size=1,color="black",curvature = 1,
arrow = arrow(length = unit(0.03,"npc"),ends="first"))
- curvature 曲线弯曲程度
- ends="first"改变箭头方向
- type="closed"对箭头进行填充
实际案例展示
自定义主题
rm(list=ls())
pacman::p_load(tidyverse,reshape2,ggsci)
theme_niwot <- function(){
theme_bw() +
theme(text = element_text(family = "Times"),
axis.line.x = element_line(color="black"),
axis.line.y = element_line(color="black"),
axis.text.x = element_text(family = "Times",size=12,face="plain"),
axis.text.y = element_text(family = "Times",size=12,face="plain"),
panel.border = element_blank(),
axis.title.x = element_text(margin = margin(t = 10),size=13,
family = "Times",color="black"),
axis.title.y = element_text(margin = margin(r = 10),size=13,
family = "Times",color="black"),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.y = element_blank(),
plot.margin = unit(c(1, 1, 1, 1), units = ,"cm"),
legend.text = element_text(size = 12,family ="Times"),
legend.title = element_blank(),
legend.key = element_blank(),
panel.background = element_rect(fill = "white"),
legend.background = element_rect(color = "black",
fill = "transparent",size = 2, linetype = "blank"))
}
数据整合
iris_mean <- iris %>% melt() %>%
summarize(avg = mean(value,na.rm = T)) %>% pull(avg)
mean <- iris %>% melt() %>%
group_by(variable) %>% summarise(mean=mean(value)) %>%
mutate(y1=iris_mean)
#pull 提取单列
可视化操作
iris %>% melt() %>%
ggplot(aes(variable,value))+
geom_point(aes(color = Species),
position = position_jitter(width = 0.2),
size =2,alpha = 0.5)+
scale_color_npg()+theme_niwot()+
theme(legend.position = "none")+
geom_point(data=mean,aes(x=variable,y=mean),size=5,
color=c("#E41A1C","#1E90FF","#FF8C00","#4DAF4A"))+
geom_hline(aes(yintercept=iris_mean),
color = "gray70",size = 1)+coord_flip()+
geom_segment(data=mean,aes(x = variable, xend = variable,
y =y1,yend =mean),size=0.8,
color=c("#E41A1C","#1E90FF","#FF8C00","#4DAF4A"))+
annotate("text", x =4.3, y = 7, family = "Times",
size = 4, color = "gray20",
label = "The mean number of\niris observations was 3.46")+
annotate("text", x = 3.8, y = 6, family = "Times",
size = 4, color = "gray20",
label ="The mean number of\nPetal.Length observations was 3.76")+
annotate(
"text", x = 1, y = 1.2,
family = "Times", size =4, color = "gray20",
label="The mean number of\nPetal.Length observations was 3.06")+
geom_curve(aes(x =4.1,y = 7,yend =3.46,xend = 3.6),
arrow = arrow(length = unit(0.03, "npc"),type="closed"),
size = 0.5,curvature=0.2,
color = "grey30")
可以通过创建数据框的方式添加曲线,在此就不一一展示了