> ggplot(kk, aes(x=aa, y=bb))+geom_point() > ggplot()+geom_point(data=kk, aes(x=aa, y=bb)) '#效果和上一句相同 image.png 2. 标记图中的某个点 >kk aa bb111.190022-0.894033-0.7653440.9845550.9168>ggplot()+geom_point(data=kk,aes(x=aa,y=bb))+geom_point(aes(x=kk[3,1],y=...
1、ggplot2绘制基础条形图和线形图(basicbarorlinegraphs)1.1、默认条形图1.2、不同柱子上不同色、添加图例1.3、柱子添加黑色外框1.4、给条形图添加标题、设置柱子填充色、关闭图例1.5、数据集计数条形图1.6、基础线性图1.7、线性图添加数据点1.8、设置线形图线型及点的形状1.9、设置线性图的标题1.10、多组数据堆积条...
GGally:GGallyextends ggplot2 for visualizingcorrelation matrix,scatterplot plot matrix,survival plotand more. ggRandomForests: Graphical analysis ofrandom forestswith the randomForestSRC and ggplot2 packages. ggdendro: Create dendrograms and tree diagrams using ggplot2 ggmcmc: Tools for Analyzing MCMC ...
geom_boxplot(): Box plot geom_violin(): Violin plot geom_dotplot(): Dot plot geom_jitter(): Jitter charts geom_line(): Line plot geom_bar(): Bar plot geom_errorbar(): Error bars geom_point(): Scatter plot geom_smooth(): Add smoothed curve geom_quantile(): Add quantile lines geo...
1.ggplot2 - alpha参数 library(ggplot2) data(iris) ggplot(iris, aes(x = Sepal.Length, y = Petal.Length,...scatter plot with alpha 2.plot修改 plot画图的时候,直接修改col就可以,一个比较方便的方法是用rgb()函数。...如下所示: 没有透明度: plot(x = iris$Sepal.Length, iris$Petal.Length,...
ggplot(data, aes(x, y, label=label))+# ggplot2 plot with labelsgeom_point()+geom_text(aes(label=label), hjust=-0.5) As shown in Figure 2, the previous syntax created a ggplot2 scatterplot with labels. Example 3: Add Labels to Some Points in ggplot2 Scatterplot ...
qplot(): Quick plot with ggplot2 Scatter plots Bar plot Box plot, violin plot and dot plot Histogram and density plots Box plots Basic box plots Box plot with dots Change box plot colors by groups Change box plot line colors Change box plot fill colors ...
title="Scatterplot with overlapping points", caption="Source: midwest") 上图中其实有很多点是重合的 原始数据是整数 1 dim(mpg) 用jitter_geom()画抖动图 重合的点在原先的位置基于一定阈值范围(width)随机抖动 1 2 3 4 5 6 7 8 9 10 11 12 library(ggplot2) data(mpg, package="ggplot2")...
(formula=formula,r2=r2,stringsAsFactors=FALSE)#plot the simple scatterplot>p<-ggplot(dat,aes(x=degree,y=complex,colour=degree>=63))+geom_point(shape=19)+xlab("Degree of WD40 proteins")+ylab("Number of complexes")#linear regression analysis>dat.lm<-lm(complex~degree,data=dat)#add a ...
Scatterplot with regression line #Add linear regression line ggplot2.scatterplot(data=df, xName='wt',yName='mpg', addRegLine=TRUE, regLineColor="blue") #Add the 95% confidence region ggplot2.scatterplot(data=df, xName='wt',yName='mpg', addRegLine=TRUE, regLineColor="blue"...