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...
#Scatter plots(sp)sp <- ggscatter(mtcars, x="wt", y="mpg",add="reg.line",#Add regressionlineconf.int= TRUE,#Add confidence intervalcolor ="cyl", palette ="jco",#Color by group cylshape ="cyl"#Change point shape by groups cyl)+ stat_cor(aes(color=cyl), label.x =3)#Add corr...
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,...
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...
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)", ...
data("midwest", package = "ggplot2") # Scatterplot # 设置x轴和y轴范围 gg <- ggplot(midwest, aes(x=area, y=poptotal)) + geom_point(aes(col=state, size=popdensity)) + geom_smooth(method="loess", se=F) + xlim(c(0, 0.10)) + ylim(c(0, 500000)) + labs(subtitle="Area Vs ...
#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 ...
线(line,vline,abline,hline,stat_function等):一般是基于函数来处理位置 射(segment):特征是指定位置有xend和yend,表示射线方向 面(tile, rect):这类一般有xmax,xmin,ymax,ymin指定位置 棒(boxplot,bin,bar,histogram):往往是二维或一维变量,具有width属性 ...
# loess method: local regression fitting p3 <- ggscatter(df, x = "wt", y = "mpg", add = "loess", conf.int = TRUE, cor.coef = TRUE, # Add correlation coefficient. see ?stat_cor cor.coeff.args = list(method = "spearma...