ggplot2分面图形自定义添加回归曲线R值

R语言数据分析指南

发布于 2022-12-20 19:44:47

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发布于 2022-12-20 19:44:47

❝本节来介绍如何自定义给分面图形添加R值与P值，通过两个案例来进行展示❞

加载R包

library(tidyverse)
library(gapminder)
library(ggpmisc)
library(ggsci)
library(grid)

导入数据

df <- read_tsv("data.xls") %>% filter(!continent %in% c("Oceania","Americas"),year >=1982)

数据可视化

❝在这个案例中我们介绍使用「stat_quant_eq」函数自动添加拟合曲线的R值与P值❞

df %>% ggplot(aes(gdpPercap,lifeExp,color=continent))+
  geom_point(size=2.5,aes(color=continent))+
  geom_smooth(aes(color=continent),method = 'lm', se = TRUE, show.legend=FALSE)+
  facet_wrap(.~year,scales="free_x",nrow=2,ncol=3)+
  scale_color_npg()+
  stat_poly_eq(method = 'lm',
               aes(label=paste(after_stat(rr.label),
                               after_stat(p.value.label),sep = "*\", \"*")),
               size=3)+
  labs(x=NULL,y=NULL)+
  theme_bw()+
  theme(axis.text=element_text(colour='black',size=9),
        legend.position = c(0.94,0.1),
        legend.background = element_blank(),
        legend.key = element_blank(),
        legend.title = element_blank())

❝可以看到使用「ggpmisc::stat_poly_eq」函数很轻松的添加上了R值与P值，但是实际中也许会存函数无法自动添加的情况，那么就需要使用代码自定义去添加，如果图表只有一个那样操作很是轻松，但若是图表采用分面的形式绘制那么就需要自定义函数来添加文本 ❞

自定义注释函数

annotation_custom2 <- function (grob, xmin = -Inf, xmax = Inf, ymin = -Inf, ymax = Inf, data) 
{
  layer(data = data, stat = StatIdentity, position = PositionIdentity, 
        geom = ggplot2:::GeomCustomAnn,
        inherit.aes = TRUE, params = list(grob = grob, 
                                          xmin = xmin, xmax = xmax, 
                                          ymin = ymin, ymax = ymax))
}

构建文本信息

grob1 <- grobTree(textGrob(expression(paste(italic(R^2),"=0.25, ",italic(p),"<0.001")),
                           x=0.1,y=0.95, hjust=0,gp=gpar(col="#DC0000FF", fontsize=10)))

grob2 <- grobTree(textGrob(expression(paste(italic(R^2),"=0.29, ",italic(p),"<0.001")),
                           x=0.1,  y=0.88, hjust=0,gp=gpar(col="#4DBBD5FF", fontsize=10)))

grob3 <- grobTree(textGrob(expression(paste(italic(R^2),"=0.51, ",italic(p),"<0.001")),
                           x=0.1,  y=0.82, hjust=0,gp=gpar(col="#00A087FF", fontsize=10)))

案例二

df %>% ggplot(aes(gdpPercap,lifeExp,color=continent))+
  geom_point(size=2.5,aes(color=continent))+
  geom_smooth(aes(color=continent),method = 'lm', se = TRUE, show.legend=FALSE)+
  facet_wrap(.~year,scales="free_x",nrow=2,ncol=3)+
  scale_color_npg()+
  labs(x=NULL,y=NULL)+
  theme_bw()+
  theme(axis.text=element_text(colour='black',size=9),
        legend.position = c(0.94,0.1),
        legend.background = element_blank(),
        legend.key = element_blank(),
        legend.title = element_blank())+
  annotation_custom2(grob1,data=df %>% filter(year==1982))+
  annotation_custom2(grob2,data=df %>% filter(year==1982))+
  annotation_custom2(grob3,data=df %>% filter(year==1982))