#最后scale_size诸多设置也可以用scale_size_area()进行设置。 1 #接下来,了解下scale_alpha()相关设置,基本上和scale_size()类似p+geom_point()+scale_alpha("花瓣宽度",breaks=c(0.2,0.4,0.6,0.8))#强行对透明度设置自定义分组 1 2 p+geom_point()+scale_alpha("花瓣宽度",breaks=c(0.2,0.4,0.6,0.8...
sizes <- expand.grid(size = seq(0,6), stroke = seq(0,6)) ggplot(sizes, aes(size, stroke, size = size, stroke = stroke)) + geom_point(shape = 21, fill = "red",color="blue") + scale_size_identity() + scale_x_continuous(n.breaks = 6) +scale_y_continuous(n.breaks = 6)...
scale_size(name,breaks,labels,limits,range,trans,guide) scale_size_area(...,max_size) scale_size_manual 1. 2. 3. 4. 5. 6. 7. 示例。 ggplot(mpg,aes(displ,hwy,size=hwy))+ geom_point()+ scale_size(name = 'hwy size',breaks = c(12,24,44), labels = c('low','middle','hig...
breaks 将数据进行指定分组,搭配参数label可以修改组名 ggplot(mpg, aes(displ, hwy))+geom_point()+ scale_x_continuous(breaks = c(2, 4, 6),label = c("two", "four", "six")) limits 限定坐标轴的刻度范围,和函数xlim效果一样 library(gridExtra)p1 <- ggplot(mtcars, aes(wt, mpg))+geom_po...
# 3.1 坐标轴标尺 lims(x,y)/xlim()/ylim() scale_x_continuous(breaks, labels,limits) # x轴...
p1 <- ggplot(mtcars, aes(wt, mpg)) geom_point() scale_x_continuous(name='AAA')p2 <- ggplot(mtcars, aes(wt, mpg)) geom_point() labs(x='BBB')grid.arrange(p1,p2,ncol=2) breaks 将数据进行指定分组,搭配参数label可以修改组名 ggplot(mpg, aes(displ, hwy)) geom_point() scale_x_...
element_text(face, color, size, angle): 修改文本风格 element_blank(): 隐藏文本 修改刻度标签等 移除刻度标签等 当然可以自定义坐标轴了 离散非连续坐标轴 scale_x_discrete(name, breaks, labels, limits) scale_y_discrete(name, breaks, labels, limits) ...
scale_fill_gradient(low='', high='', breaks=, limits=) low和high是用于指定最小和最大色阶 breaks是用于将填充颜色进行分割(cut) limits是限定色阶的范围 3.3添加随机扰动点 当散点图中其中一个数据轴或两个数据轴都对应于离散型变量时,也会出现图形重叠的情况,因此可以给数据添加随机扰动点 ...
* minor_breaks 表示指定细网格线对应位置,细网线没有标签对应,没有labels参数 * sec.axis 表示是否开启次坐标轴 例: library(ggplot2) p1 <- ggplot(mpg, aes(displ, hwy)) + geom_point() p1 p1 + scale_x_continuous(name = "发动机排量/L", limits = c(2,6), breaks = c(2, 4, 6), lab...
Sepal.Width)) + geom_boxplot(fill = 'steelblue', outlier.colour = 'red', outlier.shape = 15, width = 1.2) + theme(axis.title.x = element_blank()) + scale_x_discrete(breaks = NULL) + stat_summary(fun.y = 'mean', geom = 'point', shape = 18, colour = 'orange', size = ...