R可视化：dotplot图美化

相比boxplot图而言，dotplot能更好展示数据分布情况，记录下美化dotplot的经历。更多知识分享请到 https://zouhua.top/。

加载包

library(dplyr)
library(tibble)
library(ggplot2)

grp <- c("setosa", "versicolor")
grp.col <- c("#2D6BB4", "#EE2B2B")

导入数据

dat <- iris %>% dplyr::filter(Species!="virginica") %>%
  mutate(Species=factor(Species, levels = grp))

可视化

ggplot(dat, aes(x=Species, y=Sepal.Length))+
    # dotplot 
    geom_dotplot(aes(color=Species, fill=Species), 
                 binaxis='y', stackdir='center', dotsize = .7)+
    # errorbar 
    stat_summary(fun.data=mean_sdl, fun.args = list(mult=1), 
        geom="errorbar", width=0.1, size=1) +
    # median line : crossbar  
    stat_summary(fun=median, geom="crossbar", color="black", size=.4, width=.4)+
    labs(x="")+
    scale_y_continuous(breaks = seq(3, 7, 0.5),
                       limits = c(3, 8),
                       expand = c(0, 0))+
    scale_fill_manual(values = grp.col)+
    scale_color_manual(values = grp.col)+
    guides(fill=F, color=F, shape=F)+
    # significant levels 
    annotate("segment", x = 1, xend = 2, y = 7.4, yend = 7.4, color = "black", size=1)+
    annotate("text", x = 1.5, y = 7.8, color = "black", size=6, label = "p<0.05")+  
    theme_classic()+
    theme(axis.title.y = element_text(face = 'bold',color = 'black',size = 14),
          axis.title.x = element_text(face = 'bold',color = 'black',size = 14,
                                      vjust = -1.2),
          axis.text.y = element_text(face = 'bold',color = 'black',size = 10),
          axis.text.x = element_text(face = 'bold',color = 'black',size = 12),
          axis.line = element_line(color = "black", size = 1),
          panel.grid = element_blank())

参考

1. errorbar guide

参考文章如引起任何侵权问题，可以与我联系，谢谢。