❝本节来介绍如何使用ggplot2来个性化绘制气泡图,数据无实际意义,整个过程仅参考。希望对各位观众老爷能有所帮助。「代码会整合上传到学习交流群」,购买过小编R数据可视化文档的朋友可在所加的交流群内获取下载,有需要的朋友可关注文中介绍加入交流群。 ❞
❝1.使用刻度条来展示y轴并进行渐变色填充,增加正负号来展示数据变化情况 2.散点通过外部轮廓颜色与内部填充颜色来定义两个变量 3.添加虚线来展示平均值 相对于以往的气泡图,此图可展示更多的数据信息,同时又具体些许新意 ❞
library(tidyverse)
library(scales)
library(MetBrewer)
library(magrittr)
library(ggpubr)
library(ggnewscale)
sessionInfo()
df <- read_tsv("data.xls") %>% filter(year %in% c(1997)) %>%
mutate(gdpPercap2=gdpPercap/500)
ggplot(df,aes(gdpPercap2,lifeExp))+
geom_smooth(method = lm,formula = y ~ splines::bs(x, 3),se = FALSE)+
# 添加点
geom_point(aes(size=pop,fill=lifeExp,color=continent),
pch=21)+
scale_fill_gradientn(colors=rev(met.brewer("Monet")))+
scale_color_manual(values=c("#E41A1C","#1E90FF","#FF8C00","#4DAF4A","#984EA3"))+
guides(size="none",fill="none")+
theme_minimal()+
labs(x="gdpPercap",y="lifeExp")+
theme(
plot.margin=unit(c(0.3,0.3,0.3,1),units=,"cm"),
axis.line.x = element_line(color = "#999999",size = 0.2),
axis.line.y=element_blank(),
panel.grid.minor = element_blank(),
panel.grid.major = element_line(size = 0.2,color = "#e5e5e5"),
axis.title.y = element_blank(),
axis.title.x = element_text(margin = margin(t =8), size = 11,color="black"),
axis.text.x = element_text(color="black",margin = margin(t =5)),
axis.text.y= element_text(color="black",margin = margin(r =-22)),
legend.title = element_blank(),
legend.key=element_blank(),
legend.text = element_text(color="black",size=10,margin = margin(l=0)),
panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank())+