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R绘图模板——散点+回归线+误差线+显著性！！！
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rm(list = ls())setwd("D:/桌面/散点+回归线+误差线+显著性")
#加载R包library(ggplot2) # Create Elegant Data Visualisations Using the Grammar of Graphicslibrary(ggpubr) # 'ggplot2' Based Publication Ready Plotslibrary(ggpmisc) # Miscellaneous Extensions to 'ggplot2'2、加载数据（随机编写，无实际意义）：df <- read.table("data.txt", header = 1, check.names = F)#分别求取size,X和Y的均值X <- aggregate(X ~ group, df, function(x) c(mean = mean(x), sd = sd(x)))Y <- aggregate(Y ~ group, df, function(x) c(mean = mean(x), sd = sd(x)))size <- aggregate(size ~ group, df, function(x) c(mean = mean(x), sd = sd(x)))# 保留两位小数X$X <- round(X$X, 2)Y$Y <- round(Y$Y , 2)size$size <- round(size$size , 2)#整理绘图数据data <- data.frame( group=X$group, X=X$X[,1], X_error=X$X[,2], Y=Y$Y[,1], Y_error=Y$Y[,2], size=size$size[,1])#绘图ggplot(data, aes(X, Y))+ #水平方向误差线 geom_errorbar(aes(xmin=X-X_error,xmax=X+X_error), linewidth = 0.8, width = 0)+ #垂直方向误差线 geom_errorbar(aes(ymin=Y-Y_error,ymax=Y+Y_error), linewidth = 0.8, width = 0)+ #散点 geom_point(aes(color = group, size = size))+ #回归线 geom_smooth(method = "lm", color="red", fill = "red", se=T, formula = y ~ x, linetype=1, alpha=0.2)+ #回归方程及R2、p值 # stat_cor(method = "pearson",label.x = 17, label.y = 27, size=4.5)+ stat_poly_eq(formula = y ~ x, aes(label = paste(eq.label,after_stat(adj.rr.label),..p.value.label..,sep = "~~~~")), parse = TRUE, size=4.5, label.x = "left")+ #点大小范围 scale_size_continuous(range = c(3, 12))+ #图例 guides(color=guide_legend(override.aes = list(size=5,alpha=1)), size = "none")+ #标题 labs(x = "X_lab", y = "Y_lab", color = NULL)+ #主题 theme_bw()+ theme(panel.grid=element_blank(), axis.text=element_text(color='black',size=12), axis.title = element_text(color='black',size=14), legend.position = c(0.92,0.35))+ #颜色 scale_color_manual(values = c("#ff0000","#ffed00","#ff0092","#00b2a9", "#00c7f2","#dc5034","#a626aa","green","blue"))PS: 以上内容是小编个人学习代码笔记分享，仅供参考学习，欢迎大家一起交流学习。
完整代码（附带注释）及原始数据获取：
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