Scatter plot with linear regression line of best fit 图1,显示不同类别 df <- ggplot2::mpg %>% setDT() df_select <- df[cyl %in% c(4,8),] %>% .[,cyl:=as.factor(cyl)] cyl_color <- c("#1f77b4", "#ff983e") # geom_smooth的填充范围,只有数据和全图可选,而且se只会按垂直方向...
# A scatterplot with regular (linear) axis scaling sp <- ggplot(dat, aes(xval, yval)) + geom_point() library(scales) sp + scale_y_continuous(trans = log2_trans(), breaks = trans_breaks("log2", function(x) 2^x), labels = trans_format("log2", math_format(2^.x))) set.se...
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",...
3d(wt, disp, mpg, pch=16, highlight.3d=TRUE, type="h", main="3D Scatter Plot with Vertical Lines and Regression Plane") fit <- lmmpg ~ wt + disp) s3d$plane(fit) detach(mtcars 使用rgl包的plot3d()函数可创建交互式的三维散点图,通过鼠标即可对图形进行旋转。 1 2 3 4 library...
ggarrange(ggsurv$plot, ggsurv$table, heights = c(2, 0.7), ncol = 1, nrow = 2, align ="v") 改变排列图的行列 设置面板为两行两列,其中sp占据第一行的两列,bxp以及dp置于第二行的两列 ggarrange(sp,#First row with scatter plot(sp)ggarrange(bxp, dp, ncol = 2, labels = c("B","C...
Add regression lines The functions below can be used to add regression lines to a scatter plot : geom_smooth() and stat_smooth() geom_abline() geom_abline() has been already described at this link : ggplot2 add straight lines to a plot. Only the function geom_smooth() is covered in ...
今天第一幅图是散点图(scatterplot) 散点图是数据分析中非常常用的一种形式(The most frequently used plot for data analysis is undoubtedly the scatterplot);如果你想初步了解两个变量之间的关系,第一选择一定是散点图(Whenever you want to understand the nature of relationship between two variables, invari...
ggarrange(sp, #First row with scatter plot(sp) ggarrange(bxp, dp, ncol = 2, labels = c("B","C")),#Second row with box and dot plot nrow = 2, labels = "A" #Labels of the scatter plot) R包cowplot cowplot::ggdraw()可以将图形置于特定位置, ggdraw()首先会初始化一个绘图面板,...
This function creates a scatterplot with marginal distributions overlaid on the axes and results from statistical tests in the subtitle:ggscatterstats( data = ggplot2::msleep, x = sleep_rem, y = awake, xlab = "REM sleep (in hours)", ylab = "Amount of time spent awake (in hours)", ...
#Scatterplots(sp)sp<-ggscatter(mtcars,x="wt",y="mpg",add="reg.line",#Addregressionline=TRUE,#Add confidenceintervalcolor="cyl",palette="jco",#Colorbygroupcylshape="cyl"#Change point shape by groups cyl)+stat_cor(aes(color=cyl),label.x=3)#Add correlation coefficientsp ...