data.frame(x = 1:10, y = 1:10) # 创建一个基础图表对象 p <- ggplot(data, aes(x = x, y = y)) + geom_point() # 添加散点图 # 添加水平线 p <- p + geom_hline(yintercept = 5) # 添加数字标签 p <- p + geom_text(aes(x = 10, y = 5, label = "5")) # 显示图表...
...2)添加阈值线 使用geom_hline() 和 geom_vline( )参数添加阈值线 ggplot(data = data, aes(x = logFC, y = -log10(adj.P.Val...5) 标示感兴趣的基因的表达情况 将我们感兴趣的基因添加到数据的LABEL列中,假设以下几个基因是我们重点关注的基因,单独查看以下基因的表达情况 ?...呐,到这里除了...
ggplot(mpg, aes(x = displ, y = hwy, color = class)) + geom_point() + guides(color = guide_legend(title = "车辆类别", label.color = "blue")) guide_colorbar():设置渐变色条(colorbar)的属性,例如标题、刻度线、颜色等。我们可以通过传入不同的参数值来调整渐变色条的外观和布局。例如,可以...
-GDP), y = GDP)) + geom_bar(stat ='identity', color ='black', fill ='steelblue') + labs(x ='') +# 添加数值标签geom_text(mapping = aes(x = Province, y = GDP, label = GDP, vjust = -0.2)) +# 添加水平参考线geom_hline(yintercept = mean(df$GDP), color ='...
这里用到的是geom_textline函数, 一起看一下吧. dat1 %>% dplyr::filter(., Tree == 1) %>% ggplot(aes(x = age, y = circumference)) + geom_textline(label = "This is my text oh oh oh!", size = 4, vjust = -0.2, linewidth = 1, linecolor = "red4", linetype = 2, ...
geom_linerange 垂线 geom_map 绘制地图数据 geom_quantile 平滑的分位回归 geom_ribbon bar,带有垂直厚度的路径 geom_rug 边际轴须图 geom_sf 绘制可视化简单特征对象 (sf) geom_sf_label 绘制可视化简单特征对象 (sf) 添加标签 geom_sf_text 绘制可视化简单特征对象 (sf) 添加文本 geom_text 添加文本说明或者...
想到了`geomtextpath` 这个包的一个整蛊玩法:刻章```ggplot(data.frame(x = 1:100), aes(x = x)) + geom_hline(yintercept = 5, color = "red", linewidth = 1.6) + geom_hline(yintercept = 4.8, color = "red", linewidth = .6) + geom_textpath(aes(y = 3.7), label = "南京大学...
library(ggplot2)p=ggplot(mpg,aes(displ,hwy,colour=class))+geom_point()p+geom_hline(yintercept=25)+geom_vline(xintercept=3)+geom_abline(slope=3,intercept=20) image.png 2.2 文字注释——geom_text与geom_label 使用geom_text()和geom_label()也可以在图中添加文字,进而实现注释的效果。但是需要...
p1<-p+geom_hline(yintercept =0.989,color="#44758E",linetype="dashed",size=1)+geom_hline(yintercept =0.804,color="#44758E",linetype="dashed",size=1)+annotate('text',x=25,y=1,label="SNP Mean Concordance:0.989",size=3)+annotate('text',x=25,y=0.815,label="INDEL Mean Concordance...
(x=MetriCorrectetd,y=Droplets.cm2), size=0.2, colour="blue")+ geom_line(data = DF_Predicted_Density,aes(x=MetriCorrectetd,y = Predicted), size=0.8, colour = "green3", alpha = 0.8)+ facet_wrap(~ LABEL, ncol=2)+ geom_text(x = 4.5, y = 225, aes(label = R), data = df_...