ggplot(mpg, aes(x = displ, y = hwy, shape = class)) + geom_point(size = 3,color = ...
p=ggplot(dat,aes(x=X,y=Y))+ geom_point(shape="k",size=10) print(p) 3、如果shape是"." 将绘出有一个非常小的点(此时的size并没能调整到大小) p=ggplot(dat,aes(x=X,y=Y))+ geom_point(shape=".",size=20) print(p) 4如果shape是NA 则隐藏点 p=ggplot(dat,aes(x=X,y=Y))+ ge...
Key R functions List of point symbols Demo dataset Basic scatter plots Scatter plot with multiple groups ConclusionKey R functions geom_point(aes(x, y), data = NULL, shape = 19, color = "black", size = 1): ggplot2 function to create a scatter plot. scale_shape_manual(), scale_color...
enviroPCA_plot <- ggplot(enviroPCA_sites, aes(x = PC1, y = PC2)) + geom_hline(yintercept = 0, linetype = "dotted") + geom_vline(xintercept = 0, linetype = "dotted") + geom_line(aes(group = city), alpha = 0.7) + geom_point(size = 2.75, shape = 21, colour = "black...
ggsurv是一个包含两部分的list plot:生存曲线 table:风险表可以用ggarrange()进行排列这两者 ggarrange(ggsurv$plot, ggsurv$table, heights = c(2, 0.7), ncol = 1, nrow = 2) 上图中的坐标轴没有对齐,可以通过参数align来设置 ggarrange(ggsurv$plot, ggsurv$table, heights = c(2, 0.7), ncol =...
ggplot(hw,aes(x=ageYear,y=heightIn,shape=sex,fill=weightGroup))+ geom_point(size=2.5)+scale_shape_manual(values = c(20,24))+ scale_fill_manual(values = c("blue","black"),guide=guide_legend(override.aes = list(shape=25)))
stat_summary(fun=median,geom="point",size=3,shape=21,color="black",fill="white") 9、有缺口箱线图: ggplot(df,aes(group3,value))+ stat_boxplot(geom="errorbar",width=0.1,size=0.8)+ geom_boxplot(aes(fill=group3),outlier.color=NA,notch=T) ...
geom_point(size=2.5)+ scale_shape_manual(values = c(21,24))+ scale_fill_manual(values = c(NA,"orange"), guide=guide_legend(override.aes = list(shape=21))) #指定图例键的美学参数的列表 #help(scale_fill_manual) #2.6 散点图中创建渐变色系 (必须是将连续性变量映射给fill) ...
fun.args=list():可选的参数,用于指定传递给fun.xxx函数的参数 1,向点图中增加均值和中位数 # dot plot with mean points p+ stat_summary(fun.y=mean, geom="point", shape=18, size=3, color="red") # dot plot with median points
point range f+geom_pointrange() 1. 点图+误差棒 g <- ggplot(df, aes(x=dose, y=len))+ geom_dotplot(binaxis = "y", stackdir = "center") 1. 2. 添加geom_crossbar() g+stat_summary(fun.data = mean_sdl, fun.args = list(mult=1), geom="crossbar", color="red", width=0.1)...