#参考https://blog.csdn.net/zhouhucheng00/article/details/106413401

#加载所需的包并设置主题样式

library(ggplot2)

library(ggpubr)

library(ggpmisc)

theme_set(ggpubr::theme_pubr()+

            theme(legend.position = "top"))

#加载目标数据

df<-read.csv("richness.csv", header = T)

#数据样式

#使用 ggscatter() 也可以轻松绘制散点图，并可以使用 stat_cor() 自动添加相关系数和显著性水平(P值)。

p<-ggscatter(df, x = "richness", y = "plant",

          add = "reg.line", conf.int = TRUE,    

          add.params = list(color = "blue", fill = "lightgray")

                    )

p + stat_cor(method = "spearman", label.x = 0.07, label.y = 0.7)

p + stat_cor(p.accuracy = 0.001, r.accuracy = 0.01)

p<-p + stat_cor(p.accuracy = 0.001, r.accuracy = 0.01)

p<-p + labs( x = "Microbial community richness", y = "Plant growth promotion

by microbial communities (%)")

#图片保存

ggsave(p,filename = "richness.jpg",width = 4,height =4)

#图片展示